NLSM -Older and Young Men

This section describes (1) the separately administered survey that collected information from the high schools attended by respondents in the Young Men cohorts and (2) the set of created variables detailing characteristics of up to three colleges attended by respondents in the Young Men cohorts. Comparable data are available for respondents in the Young Women cohort. No similar surveys were administered for the Older Men.

• High School Survey
• College Survey

High School Survey

Information on secondary schools was collected during 1968 by the Census Bureau via a separate school survey mailed directly to the 3,030 schools attended by respondents in the Young Men and Young Women cohorts. After follow-up procedures were conducted to maximize responses, some information is available for approximately 95% of the schools attended by the members of these two cohorts; complete information is available for 75% of the schools (Kohen 1973). Data were collected on (1) characteristics of the schools (type of school, total student enrollment by grade, annual expenditure per pupil, number of books in the school library); (2) characteristics of the school's teachers and counselors (number of full-time teachers and counselors, annual salary for an inexperienced teacher, presence of a vocational guidance program); and (3) respondents' performance on various aptitude and intelligence tests as well as their absenteeism and school disciplinary record. Constructed variables including an index of school quality, number of books per pupil, number of students per full-time teacher, number of counselors per 100 students, percent black/Spanish-American student enrollment, and percent black faculty are also available for one or both cohorts. The "Aptitude, Achievement & Intelligence Scores" and "Crime, Delinquency & School Discipline" sections provide additional information on those subsets of the school survey variables.

College Survey

A series of variables provides information about the colleges attended by respondents in the Young Men and Young Women cohorts during the late 1960s and early 1970s. Data on schooling collected during the regular surveys (e.g., grade attending, when entered this school, names and locations of colleges, highest grade completed) were merged with information detailing the characteristics of each college to form this set of created variables called the "College Survey."

The following variables were created for each of up to three colleges attended (i.e., the first college attended, the most recent college attended as of 1971, and the college attended for the longest time between the first and most recent college), the last year the respondent attended that college, state identification code for the college's location, whether the college was private or public, the type of college or university, the highest college degree offered at the institution, the race/sex composition and socioeconomic status of the student body, an index of institutional selectivity, number of books in the library, percentage of faculty with a Ph.D., expenditures per full-time student, ratio of students to faculty, and an index indicating whether the college was "below average," "average," or "above average" in six areas of occupational/career orientation.

References

Astin, Alexander. Who Goes Where to College. Chicago, IL: Science Research Associates, 1965.

Kohen, Andrew. "Determinants of Early Labor Market Success among Young Men: Race, Ability, Quantity and Quality of Schooling." Ph.D. Dissertation, The Ohio State University, 1973.

All variables present on a main file data set, accessed through NLS Investigator, are documented via: (1) a cohort-specific codebook and (2) an accompanying codebook supplement. This section describes these components and discusses the important types of information found within each.

Codebook

The codebook is the principal element of the documentation system and contains information intended to be complete and self-explanatory for each variable in a data file. Codebook information can be viewed with the use of NLS Investigator by clicking on a variable's reference number once a list of variables has been selected.

Every variable is presented within the documentation as a block of information called a "codeblock." Codeblock entries depict the following information: a reference number, variable title, coding information, frequency distribution, reference to the questionnaire item or source of the variable, and information on the derivation for created variables. The codeblocks of many variables include special notes containing additional information designed to assist in the accurate use of data from that variable.

Codebooks are arranged by reference number. Variables are first grouped according to survey year. Within each survey year, those variables related to the interview (e.g., interview method, interview date, reason for noninterview, sampling weight, etc.) appear first, followed by variables picked up directly from the questionnaire and Information Sheet. In general, created and edited variables appear last, although the created environmental variables are grouped with variables related to the interview in the early survey years.

The following common types of information for each variable within a codeblock will be discussed in this section: coding information, multiple responses, missing responses, derivations, frequency distribution, questionnaire items (question numbers), universe information, and valid values range.

Coding information

Each codeblock entry presents the set of legitimate codes that a variable may assume along with a text entry describing the codes. Users should note that coding information in the codeblock for a given variable is not necessarily consistent with the codes found within the questionnaire or for the same variable across years. Use only the codebook coding information for analysis. The following types of code entries occur in NLS codeblocks:

Dichotomous variables

Dichotomous or yes/no variables that are uniformly coded "Yes" = 1, "No" = 0. Some dichotomous variables in the 1990 Older Men survey were reformulated to permit this convention to be followed.

Discrete variables

Discrete (categorical), as in the case of the categories of grade level in 'Highest Grade Attended, 66':

• 0 = None
• 1 = First grade
• 2 = Second grade
• 3 = Third grade
• 4 = Fourth grade
• 5 = Fifth grade
• 6 = Sixth grade
• 7 = Seventh grade
• 8 = Eighth grade
• 9 = Ninth grade
• 10 = Tenth grade
• 11 = Eleventh grade
• 12 = Twelfth grade
• 13 = First year college
• 14 = Second year college
• 15 = Third year college
• 16 = Fourth year college
• 17 = Fifth year college
• 18 = Sixth+ years college
• -1 = Elementary, year unspecified
• -2 = High school, year unspecified
• -3 = College, year unspecified

Continuous variables

Continuous (quantitative), as in the case of 'Hourly Rate of Pay at Current or Last Job 66 *KEY*' For continuous variables, the responses are presented in the codebook using a convenient class interval.

Note: 000001 thru 999999 rate with two implied decimal places

• 0
• 1-499
• 500-999
• 1000-1499
• 1500-1999
• 2000-2499
• 2500-2999
• 3000-3499
• 3500-3999
• 4000-4499
• 4500-4999
• 5000+

Combined quantitative-qualitative variables 

Combined quantitative-qualitative variables, as in the variables that are ostensibly quantitative but which may have several nonquantitative (categorical) responses, utilize positive integers equaling the actual values for the quantitative responses and negative values, beginning with -1, for the qualitative (categorical) responses. For example, the Older Men variable 'Expected Age of Retirement, 66' is coded as follows:

• 45 thru 99 = 45-99 years
• -1 = Age not given
• -2 = Will not retire; don't plan to stop working
• -3 = Already retired

Multiple responses

Response categories to multiple entry questions found in certain Original Cohort job search, discrimination, and health questions have been coded in a geometric progression. More than one response was possible to, for example, the question "What were you doing in the past four weeks to find work?" The response categories to that question were coded as follows:

• 1 = Checked with public employment agency
• 2 = Checked with private employment agency
• 4 = Checked with employer directly
• 8 = Checked with friends or relatives
• 16 = Placed or answered ads
• 32 = Other method

Multiple responses are then coded for each respondent by adding the individual codes, which yields a unique value for each combination. Such multiple entry variables are identified by an asterisk (*) next to the answer categories in the questionnaire. If a multiple entry has only a few unique combinations, the codebook will specify the exact combinations; those with many combinations need to be unpacked. Methods of unpacking such multiple entry variables are presented in Appendix C at the end of this guide. See Appendix C: How to Unpack Multiple Entries to learn more about this process.

Missing responses

The following conventions were used to treat nonresponse in interviews with the Older and Young Men.

"NA" is the convention used to describe the absence of a valid response where (1) the respondent is not in the applicable universe or (2) the respondent refused to respond or interviewer, coding, transcribing, or data entry error occurred. NA codes are typically treated as missing data.

• NA is assigned a value of -128 if valid responses to a question or created variable range from -126 to +127 inclusive.
• NA is assigned a value of -999 if valid responses fall outside the range of -126 to +127.

Note: Refusals were also coded as -1 for some income items and other sensitive questions during PAPI interviews; however, -1 has other meanings on other questions, such as 'Highest Grade Attended, 66' in Figure 3.3.1. Users should consult the codebook before working with variables that include -1 values.

"DK" is the convention used to denote a "don't know" response; these codes are typically treated as missing data.

• DK is assigned a value of -127 if valid responses range from -126 to +127.
• DK is assigned a value of -998 if valid responses fall outside the range of -126 to +127.

Note: "NEGATIVE" is a convention used in the codebook that provides the frequency of negative responses that are not defined as NA or DK (i.e., missing).

Derivations

The decision rules employed in the creation of constructed variables have been included, whenever possible, in the codebook under the title "DERIVATIONS." This information is designed to enable researchers to determine whether available constructs are appropriate to their needs. In the 'Hourly Rate of Pay at Current or Last Job 66 *KEY*' example, the derivation describes in detail the questionnaire items used to create the variable. If the derivation is too lengthy to be included in the codebook, the codeblock instead refers users to the supplemental documentation item that contains variable creation information. In the case of 'Highest Grade Attended, 66', no derivation is shown because this variable is picked up directly from the questionnaire.

Frequency distribution

In the case of discrete (categorical) variables, frequency counts are normally shown in the first column to the left of the code categories. In the case of continuous (quantitative) variables, a distribution of the variable is presented using a convenient class interval. The format of these distributions varies. In the case of 'Hourly Rate of Pay at Current or Last Job 66 *KEY*,' the frequency count is straightforward. There are twelve categories; the maximum category shown is 5000 and above (since two decimal places are implied, the figure 5000 represents $50.00 and above), for which there is a frequency count of 0.

Questionnaire item

"Questionnaire item" is a generic term identifying the printed source of data for a given variable. A questionnaire item may be a question, a check item, or an interviewer's reference item appearing within one of the survey instruments. In 'Highest Grade Attended, 66', the questionnaire item is 48A.

Universe information

Universe information for the Original Cohort data sets is printed as separate line items in the codebook for each survey through 1976. Both sample variables present universe information at the bottom of the codeblock; in Figure 3.3.1, for example, 47 respondents do not have information available. Subsequent to 1976, universes can be tracked by referring to the flowchart associated with a particular year's survey.

Valid values range

Depicted below the frequency distribution is information relating to the range of valid values for that particular distribution. "MINIMUM" indicates the smallest recorded value exclusive of "NA" and "DK." Example "MAXIMUM" indicates the largest recorded value. In the case of the created variable example (Figure 3.3.2), 'Hourly Rate of Pay at Current or Last Job 66 *KEY*,' this value is 4615 with two implied decimal places, or $46.15.

Topcoding and asset values

To insure respondent confidentiality, income variables exceeding particular limits are truncated each survey year so that values exceeding the upper limits are converted to a set maximum value. These upper limits vary by year and cohort, as do the set maximum values. From 1966 through 1970, upper limit dollar amount variables were converted to set maximum values of 990, 999, 9990, 9999, 999900, or 999999. From 1971 through 1980, upper limit variables were set to maximum values of 50000, and from 1981 to 1983 the set maximum value was 50001. From 1966 through 1980, asset variables exceeding upper limits were truncated to 999999, and beginning in 1981 assets exceeding one million were converted to a set maximum value of 999997. In the 1990 survey of the Older Men, Census also topcoded selected asset items if it considered that release of the absolute value might aid in the identification of a respondent. This topcoding was conducted on a case by case basis with the mean of the top three values substituted for each respondent who reported such amounts.

Codebook supplements

Variable creation procedures and supplemental coding information are provided within each cohort's Codebook Supplement. There are separate codebook supplements for the Older Men and Young Men cohorts. Choose a cohort below to review the corresponding codebook supplement:

• Older Men Codebook Supplement
• Young Men Codebook Supplement

Older and Young Men cohort variables (as well as the variables from the other NLS cohorts) are accessed using NLS Investigator, which is available as a Web application. The main application of NLS Investigator is to access NLS variables for the purposes of identifying, selecting, extracting, and/or running frequencies or cross-tabulations. This interface allows the researcher to connect to a database and perform variable extractions without installing any software on a local computer.

Through a personal online account, a researcher's selected variable tagsets, frequencies, and extracts are available for a specified period of time from any computer location with Web access. A tagset is a collection of specific variables saved by the user for use at a later date. Because there is one central data source for all users, researchers will have the assurance that they are always working with the most up-to-date data, and that any necessary corrections will be immediate and universal.

This section is divided into a discussion of the procedures used to develop sample weights and a section on the practical application of these weights. Before using NLS data in analysis, researchers should consult the practical usage discussion to determine when weighting of data is appropriate. Sample-based weights in each of the NLS cohorts were designed to reflect the underlying population in the year in which each cohort was originally surveyed. Individual case weights were assigned to yearly interviews in such a way as to produce group estimates which are demographically representative of each cohort's base year population when used in tabulations.

Base-year sampling weights

Population data derived from the NLS are based on multi-stage ratio estimates. The first step was to assign each sample case a basic weight consisting of the reciprocal of the final probability of selection. This probability reflects the differential sampling by race within each stratum of the four cohorts.

The base year weights for all those interviewed were adjusted to account for the overrepresentation of blacks in the sample as well as for persons who were not interviewed in the initial survey. This adjustment was made separately for each of eight groupings for the Older Men (based on the four Census regions [Northeast, North Central, South, West] by urban-rural residence) and 24 groupings for the Young Men (based on the four Census regions, race [non-black/black], and three place of residence groupings [urban, rural farm, and rural nonfarm]).

In the first stage of ratio weight adjustment, differences at the time of the 1960 Census between the distribution by race and residence of the population as estimated from the sample PSUs and that of total population in each of the four major regions of the country were taken into account. Using 1960 Census data, estimated population totals by race and residence for each region were computed by appropriately weighting the Census counts for PSUs in the sample. Ratios were then computed between these estimates (based on sample PSUs) and the actual population totals for the region as shown by the 1960 Census.

In the second stage ratio adjustment, sample proportions were adjusted to independent current estimates of the civilian noninstitutionalized population by age, sex, and race. These estimates were prepared by carrying forward the most recent Census data (1960) to take account of subsequent aging of the population, mortality, and migration between the United States and other countries (Census Bureau 1966). The adjustment was made by race within three age groups for the Older Men and in four age groups for the Young Men.

Sampling weight nonresponse adjustment

Subsequent to the initial interview of each cohort, reductions in sample size occurred because of noninterviews. To compensate for these losses, the sampling weights of the interviewed individuals were revised. Each cohort of the NLS consists of a panel of individuals in which no new individuals were permitted to enter after the base year. As a result, all reweighting of the sample after the initial survey round was calibrated to base year population parameters. This revision was done in two stages. First, out-of-scope noninterviews in each of the years were identified by Census and eliminated from the sample of noninterviews. This group consisted of individuals who were institutionalized, who had died, who were members of the armed services, or who had moved outside the United States, i.e., individuals who were no longer members of the noninstitutionalized civilian population of the United States.

The second stage in the adjustment acknowledged the possible nonrepresentative characteristics of the in-scope interviews. For each survey year, those who were eligible but not interviewed, as well as those who were interviewed, were distributed into nonresponse adjustment cells. For the Older Men, there were 24 nonresponse adjustment cells based on 1966 data regarding race (black and non-black), length of time in residence at first interview (nine or fewer years, ten or more years, N/A), and education (N/A, eight or fewer years, nine to eleven years, twelve or more years). The Young Men cohort was divided into 30 nonresponse cells based on 1966 data using the same race and residence variables as above, but with father's occupation (white collar, service, blue collar, farm, N/A) instead of the education variables used with the Older Men. Within each of the cells, the base year sampling weights of those interviewed were increased by a factor equal to the reciprocal of the reinterview rate (using base year weights) in that year.

For the Young Men cohort, the sampling weights of those interviewed were further adjusted to account for the return to the civilian population of men who were in the armed services at the time of initial interview. This final adjustment made use of the first stage estimates described above and independent Census Bureau estimates of the civilian population by selected age categories and race.

Practical usage

The Older and Young Men cohorts were based upon stratified, multi-stage random samples with oversamples of blacks. Each case in each interview year is assigned a weight specific to that year. This weight can be interpreted as an estimate of the number of people in the population of interest that the individual in the sample represents. The following is a discussion of the ramifications of the weights when used for data analysis.

To tabulate characteristics of the sample (sample means, totals, or proportions) for a single interview year in order to describe the population being represented, it is necessary to weight the observations using the weights provided. For example, to estimate the average hours worked in 1976 by men born in 1957 through 1964, researchers would simply use the weighted average of hours worked, where weight is the 1976 sample weight. These weights are approximately correct when used in this way, with item nonresponse possibly generating small errors. Other applications for which users may wish to apply weighting, but for which the application of weights may not correspond to the intended result, include:

Samples generated by dropping observations with item nonresponse

Often users confine their analysis to subsamples for which respondents provided valid answers to certain questions. In this case, a weighted mean will not represent the entire population, but rather those persons in the population who would have given a valid response to the specified questions. Item nonresponse because of refusals, don't knows or invalid skips is usually quite small, so the degree to which the weights are incorrect is probably quite small. In the event that item nonresponse constitutes a small proportion of the variables under analysis, population estimates (i.e., weighted sample means, medians and proportions) would be reasonably accurate. However, population estimates based on data items that have relatively high nonresponse rates, such as family income, may not necessarily be representative of the underlying population of the cohort under analysis.

Data from multiple waves

Because the weights are specific to a single wave of the study, and because respondents occasionally miss an interview but are contacted in a subsequent wave, a problem similar to item nonresponse arises when the data are used longitudinally. In addition, occasionally the weights for a respondent in different years may be quite dissimilar, leaving the user uncertain as to which weight is appropriate. In principle, if a user wished to apply weights to multiple wave data, weights would have to be recomputed based upon the persons for whom complete data are available. If the sample is limited to respondents interviewed in a terminal or end point year, the weights for that year can be used.

Regression analysis

A common question is whether one should use the provided weights to perform weighted least squares when doing regression analysis. Such a course of action may lead to incorrect estimates. If particular groups follow significantly different regression specifications, the preferred method of analysis is to estimate a separate regression for each group or to use dummy (or indicator) variables to specify group membership. If one wishes to compute the population average effect of, for example, education upon earnings, one may simply compute the weighted average of the regression coefficients obtained for each group, using the sum of the weights for the persons in each group as the weights to be applied to the coefficients. While least squares is an estimator that is linear in the dependent variable, it is nonlinear in explanatory variables, and so weighting the observations will generate different results than taking the weighted average of the regression coefficients for the groups. The process of stratifying the sample into groups thought to have different regression coefficients and then testing for equality of coefficients across groups using an F-test is described in most statistics texts.

If one is unsure of the appropriate grouping, one should consult a statistician or other person knowledgeable about the data set before specifying the regression model. Note that if subgroups have different regression coefficients, a regression on a random sample of the population would be misspecified.

Custom weighting program

Every Older and Young Men survey contains a created variable that is the respondent's cross-sectional weight. Using these weights provides a simple method for users to correct the raw data for the effects of over-sampling of blacks and the initial clustering of respondents at the survey's beginning. Unfortunately, while each set of weights provides an accurate adjustment for any single year, none of the weights provide an accurate method of adjusting multiple years' worth of data. Users analyzing more than one year of Older or Young Men's data should use longitudinal weights, which improve a researchers' ability to accurately calculate summary statistics from multiple years of data.

Users can create longitudinal weights for the Older or Young Men by going to the NLS Custom Weights page. To create a set of custom weights, users select the survey years corresponding to their research and pick the "Download" button. The custom weighting program will generate a set of longitudinal weights and open a download dialog box so that users can save the weights to their computer. The resulting file contains two columns of data, with the columns separated by a blank space. The first column is the public identification (ID) number of each respondent. The second column is the weight. If the respondent did not participate in every survey checked off, then the respondent is given a weight of zero. If the respondent did participate, he is given a positive longitudinal weight.

The custom weighting program is an Internet version of the program used to create the cross-sectional weights for the original cohorts since the 1990s. The primary difference between the cross-sectional and longitudinal weighting programs is in how the list of respondents is created. In the cross-sectional case the weighting program is given a list of all people who participated in a particular survey round. In the longitudinal case the weighting program creates a "dummy" survey round where the user specifies who participated and who did not. This "dummy" round is based on the set of surveys selected. It then calculates which respondents participated in every survey round chosen by the researcher and uses that list to generate weights.

The original cohorts weighting is derived from the base year weights via a two-step process. First, all out-of-scope noninterviews, which are respondents who have died, been institutionalized, or moved outside the U.S. are eliminated from the pool of respondents who are classified as noninterviews. Second, those who are in-scope, whether or not they do an interview, are distributed into 24 cells based on race (black/non-black), length of residence at the time of the first interview (nine or less years, ten or more years, or unknown) and education (eight or less years, nine to eleven years, twelve or more years, or unknown).

These cells are then examined to see if the cells have too few respondents. If a cell has too few respondents, it is collapsed with an adjoining cell. Once the optimal number of cells is created, all of the weights associated with respondents in a particular cell are totaled. These totals are then divided to create an adjustment factor. This adjustment factor is then multiplied by each respondent's base year weight, which results in the custom longitudinal weight for a respondent.

Reference

Census Bureau. Current Population Reports. Series P-25, No. 352, November 18, 1966.

Four types of variables are present in the Older Men and Young Men data files. The type of variable affects the title or variable description which names each variable and the physical placement of the variable within the codebook. Types of variables include:

1. Direct raw responses from a questionnaire or other survey instrument.
2. Edited variables constructed from raw data according to consistent and detailed sets of procedures (e.g., occupational codings, *KEY* variables, etc.).
3. Constructed variables based on responses to more than one data item either cross-sectionally or longitudinally and edited for consistency where necessary (e.g., highest grade completed). Note: In general, the NLS does not impute missing values or perform internal consistency checks across waves. Data quality checks most often occur in the process of constructing cumulative and current status variables.
4. Variables provided by the Census Bureau or another outside organization based on sources not directly available to the user (e.g., characteristics of respondents' geographical areas).

This section describes the organization of variables within the data files and explains how to use reference numbers and variable titles while navigating the data set.

Variable documentation

Reference numbers

Every variable within the main NLS data set has been assigned an identifying number that determines its relative position within the data file and documentation system. Reference numbers, once assigned, remain constant through subsequent revisions of the files. Reference numbers are assigned sequentially, with variables from the first survey year having a lower reference number than those variables specific to the second year, and so forth. Occasionally, variables are created sometime after the year in which the data were actually collected. These variables are frequently given a reference number that reflects the year in which the actual data were gathered rather than the year the created variable was constructed. Tables 1 and 2. list reference numbers for each survey year since 1966 for the Older and Young Men cohorts.

Variable titles

Every variable within NLS main file data sets has been assigned a summary title that serves as the verbal representation of that variable throughout the hard copy and electronic documentation system. Variable titles were assigned by CHRR archivists who endeavored, within the limitations described below, to capture the core content of each variable and to incorporate within the title: (1) Key words that facilitate easy identification of comparable variables; (2) universe identifiers that specify the subset of respondents for which each variable is relevant; and (3) for some variables, reference periods that indicate the period of time (e.g., survey year or calendar year) to which these data refer.

Universe identifiers

If two ostensibly identical variables differ only in that they refer to different universes, the variable title will include a reference to the applicable universe.

Reference periods

Variable descriptions may include a phrase indicating the time period to which these data refer. The following general conventions apply:

Survey Year: When the variable title includes either the phrase XX INT (81 INT) or the year (e.g., 76) without the year being preceded by the preposition "IN," this indicates the survey year in which that variable was measured, not necessarily the year to which it applies.

Calendar Year: When a date follows a verbal description of a variable and is part of the prepositional phrase "in XX," the date identifies the calendar year for which the relevant information was collected.

Flexibility in variable title assignment for raw data items is restricted by (1) the actual wording of the question as it appears within the survey instrument; (2) precedent, i.e., how that type of variable has been titled in previous survey years; and (3) in early years, a shorter allowable length for variable titles. An attempt is also made to include key phrases in variable titles so that large groups of variables with similar or related subject matter can be easily identified.

Users should be careful not to assume that two variables with the same or similar titles necessarily have the same (1) universe of respondents or (2) coding categories or (3) time reference period. While the universe identifier and reference period conventions discussed above have been utilized, users are urged to consult the questionnaires for skip patterns and exact time periods for a given variable and to factor in the relevant fielding period(s).

Variables with similar content (e.g., information on respondents' labor force status) may have completely different titles, depending on the type of variable (raw versus created).

Finally, different archivists over a period of three decades performed the task of assigning variable descriptions to data from the NLS cohorts. While every effort has been made to maintain consistency, users may find some differences in variable titles. Two primary sources of variation exist in Original Cohort variable title assignment. The first is systematic error in which identical questions may have the same question wording across the four Original Cohorts but slightly different variable titles. The rule was to make title consistency within a cohort of highest priority. The second variation is attributed to spacing or punctuation errors. The sorting process that produces variable title listings usually places these variables near if not next to the series of interest.

How mode of interview affects question documentation

There are important differences between the content of telephone and personal interviews. In the late 1960s and early 1970s, most of the interviews were conducted in person, usually at the respondent's home. There was one attempt at a mail survey in 1968 for the Older Men and the Mature Women; however, the low response rate led to dropping that type of contact. After the first five years, the decision was made to conduct a major survey every five years and two telephone surveys during the five-year span so that problems of recall could be avoided and contact could be maintained with the respondents.

Differences in what appear to be comparable variables reflect variations in the wording of the question or the fact that the reference period for an identically worded question may be different in a personal versus a telephone interview. Questions that refer to the last five years were usually found in a personal (or five-year) interview. This difference means that some questions were only asked in the five-year surveys and some were asked only in the telephone surveys. Users conducting longitudinal analysis need to change their variable creation procedures to account for the differences in data collection between the early years of uninterrupted personal interviews and subsequent survey years when telephone interviews were used.

When analyzing data, users should remember that not all surveys were conducted during the same season of each survey year. Responses to labor force status questions, for example, may differ significantly if fielding occurred during the summer versus winter months.

The term "survey instrument" refers to: (1) the questionnaires, which serve as the primary source of data on a given respondent, and (2) documents such as the household record cards that collect information on members of the respondent's household. A unique set of survey instruments was used during each survey year to collect information from respondents. The primary variables found within the main data set of each NLS cohort were derived directly from one or more survey instruments (e.g., questionnaires, household interview cards, etc.).

The questionnaires are critical elements of the NLS documentation system and should be used by each researcher to find out the wording of questions, coding categories, and the universe of respondents asked to respond to a given question.

Certain other documents, namely Field Representative's Manuals and flowcharts, provide background information on how specific survey instruments were administered or offer the researcher additional tools for working with a questionnaire. While not actually survey instruments, these additional documents are described within this section.

Note that while the source of the majority of variables in the main NLS data sets was the questionnaire or one of the other survey instruments, certain NLS variables were created either from other NLS variables or from information found in an external data source.

Questionnaires

There are separate and distinctly different questionnaires for each survey year. Each questionnaire is organized around a set of topical subjects, the titles of which usually appear on either the first page of each section of the questionnaire or as page headers.

Each questionnaire collected two general types of information: (1) information on the actual interview (e.g., interview dates, times, and contact methods) and (2) information supplied by the respondents on various topics related to their work and life experiences. Each survey instrument was organized around core sets of questions: current labor force status, retrospective work history, attitudes, health, marital history, household composition, assets, and income. In addition, the interview schedules contained special sets of questions on a variety of topics specific to the particular stage of life: child care and fertility questions were asked in the early survey years, while later surveys emphasized retirement and pension plans.

Information sheet

Information Sheets (or flap items), located within the questionnaires, were usually designed in such a way that the interviewers could fold the sheet out to the side of the actual questionnaire and refer to the items on the flap during the interview. Various information items from previous interviews were clerically entered by Census and used by the interviewer during the survey. These included information such as name of previous employer, date of previous interview, and marital status and place of residence at the time of previous interview.

The interviewer also transcribed information recorded in the questionnaire during the current survey onto the Information Sheet. The only current survey year item that a user would need from the flap was "current marital status," transcribed from the Household Record Card in certain survey years. Items referenced frequently during the interview were more conveniently located when transferred to the flap.

Questionnaire item or question number

The questionnaire item or question number is the generic term referring to the printed source of data for a given variable. A questionnaire item may be a question, a check item, or an interviewer's reference item that appears within one of the survey instruments. Each questionnaire item has been assigned a number or a combination of numbers and letters to help the user link each variable to its location in a survey instrument.

Different designations were used within the documentation system to identify varying types of questionnaire items, as depicted in Table 1. The question number appears to the right of each variable description within the codebook. Data file users can access variable titles and codebook information via the "Accessing Data by Question Number" function.

In the vast majority of cases, the reference is to a specific question item found in the survey (e.g., 22F or 3B). The convention "CH" is used to identify interviewer check items that occur within the survey (e.g., CH B). Their purpose is to direct the interviewer to the next appropriate question. The convention "R" denotes a reference item (e.g., R2 or 12R). Typically, reference items are grouped in a section of the survey instrument called the Information Sheet, which contains information that interviewers frequently refer to during the course of an interview. Items designated "R" in the survey instruments are also designated "R" in the documentation. Finally, when an item does not include a question number, only the page number ("PG") of the questionnaire on which a particular item appears is identified (e.g., PG 1). The first page of most questionnaires contains unnumbered interview status information and transcribed Household Record Card information.

Household record cards

NLS questionnaires include the collection, during each interview, of information on the members of each respondent's household. In the PAPI years these data were collected primarily through the "Household Roster" section of the questionnaire, which in turn relies upon information provided by Census personnel and found on the separate Household Record Cards. Respondents were selected on the basis of a screening of sample households. Both the instruments used for the household data collection and the household screening instruments that were used to draw the samples of respondents are described below.

Household screener and household record cards

Prior to most PAPI interviews, Census interviewers completed or updated information found on a Household Record Card. Part of this information was transferred during the main interview to the "Household Roster" section of the questionnaire. The first Household Record Card (LGT-1, dated 2/23/1966) was the screening instrument used to select the Young Women respondents for interview. Information for this first card was gathered from any available household member, while respondents provided comparable information in subsequent surveys. Each Household Record Card (1) enumerates all persons currently living in the household; (2) records for each person: name, relationship to respondent, whether this person is considered a household member, marital status, birth date, and sex; (3) summarizes changes since the last survey in household composition; and (4) provides information on the respondent's current and/or permanent address and telephone number at the time of interview, as well as the names of people who will know how to contact the respondent at the time of the next interview.

Five versions of the paper Household Record Cards, each covering approximately three surveys, were used. While information from these cards does not, in general, appear as variables within any of the data files, certain information present on the cards detailing each respondent's current household composition is transferred to the Household Roster section of the questionnaires. In addition, certain demographic variables as of the initial survey year, notably age, birth date, race, and sex, were derived from the 1966 household screenings. Users can consult each survey's Field Representative's Manual for the specific instructions and definitions used to complete each card.

School survey (Young Men)

A supplemental survey of the last secondary school attended by Young Men respondents (as well as NLS Young Women cohort) was conducted in 1968. This special survey was mailed to the designated high schools and was designed to collect academic performance information and intelligence scores for respondents, as well as information on the programs and facilities of each high school. The instrument was called the Survey of Work Experience of Young Men and Women School Survey.

Field Representative's Manual/Interviewer's Reference Manual

Each survey instrument that went into the field was accompanied by an Interviewer's or Field Representative's Manual, which provided Census interviewers with background information on the NLS, respondent location instructions, and detailed question-by-question instructions for coding and completing the questionnaire and Household Record Cards. Note that Field Representative's Manuals do not always include all the actual questions.

Flowcharts

The questionnaires are lengthy and often present the researcher with the complex task of determining the universe of respondents asked a specific question. To assist in this task, flowcharts have been developed that graphically depict the skip patterns (the manner in which the different universes of respondents "flow" through the interview) for some questionnaires. Flowcharts are available for some post-1977 surveys as PDF files; comparable information for earlier questionnaires appears within the codebook under the heading "Universe Information."

NLS Investigator contains the most recent release of each NLS cohort. Known problems are found below. Corrections have been made to items noted in the Errata of prior releases. For further questions, please contact NLS User Services.

Errata for Custom Weighting Program

An error in the NLS Young Men custom weighting program was discovered and corrected on October 2, 2024. The program application allows an option to enter a list of IDs. A program error caused this option to be exercised in a way that resulted in only some of the IDs listed receiving weights in the output file. The created variables contained on the public release are unaffected as are yearly weights generated from the Weight Years page in the Custom Weighting program.

Errata sheet for the NLS of Young Men (1966-1981)

Revised: 09/1988

 ID   ORIG   CORR       ID   ORIG   CORR        ID   ORIG   CORR
      R8117. R8117.          R8117. R8117.           R8117. R8117.
------------------     ------------------      ------------------
 363  89960  30880     1691  32230  24965      2444 114625  18776  
1067  34609  27234     1859  54546  18846      2458 118665  38530  
1135 119916  25497     2036  59700  30500      2474  71800  13440  
1162  36480  21742     2040  36775  14752      2924 127279  31339
1377  44214  29624     2084  47425  40250      3207  85408  27448
1392  88923  29963     2093  92457  41462      3341 128890  26410
1409 216700  43300     2180  35073  13161      3849  45850  16750
1449  43457   6447     2216  70060  12068      4756  58525  21940
1531  72238  28048     2312  52318  23498      5189  80150  21630

 ID     ORIG    CORR     ID     ORIG    CORR     ID    ORIG.    CORR
	R8114.  R8114.          R8114.  R8114.         R8114.   R8114.
--------------------    --------------------    --------------------
  11     47     16      1745     57     43      3462     61     59
  22     NA     31      1750     NA     54      3491     NA     28
  36     NA     42      1751     NA     35      3508     27     29
  46     NA      8      1777     NA     22      3547     22     29
  48     NA     31      1785     NA     32      3574     NA     54
  81      5     31      1810     NA     25      3577     NA     31
  87     55     53      1834     NA     21      3587     NA     36
  91     NA     18      1858     NA     14      3588     NA     43
 104     NA      3      1860     NA     31      3602     NA     21
 216     20     42      1866     53     52      3623     NA      7
 220     44     42      1868     53     43      3627     NA      8
 241     NA     22      1893     NA     23      3653     NA     26
 250     NA     47      1903     NA     46      3656      5     31
 265     NA     30      1970     56     55      3665     NA     31
 288     NA     41      1976     30     48      3670     NA     37
 313     NA     45      1983     NA     14      3672     NA     42
 326     22     42      1993     25     35      3755     NA      4
 328     NA     48      2005     54     53      3758     NA     29
 341     51     50      2009     11     32      3764     51     48
 377     53     52      2015     17     24      3768     42     46
 381     NA     26      2019     NA     49      3777     22     25
 385     NA     41      2035     NA      3      3784     NA     37
 388     NA     38      2036     52     47      3821     NA     24
 401     NA     48      2098     NA     52      3840     NA     41
 415     NA     15      2140     NA     48      3849     NA     42
 438     12     34      2166     NA     30      3868     NA     48
 444     NA     40      2180     NA     29      3922     NA     52
 445     33     44      2202     21     41      3931     50     49
 458     52     51      2217     NA     53      3948     NA     36
 478     55     53      2224     56     55      3954     NA     20
 484     NA     44      2228     NA     21      3960     NA     50
 520     NA     29      2234     NA     33      3966     47     45
 532     NA     39      2241     NA     36      3998     NA     51
 553     NA     13      2250     49     48      4035     33     26
 624     NA     42      2263     10     33      4074     31     32
 630     NA     42      2287     38     36      4079     NA     56
 648     59     57      2288     46     51      4100     NA     55
 658     NA     55      2289     NA     54      4119     33     42
 729     NA     22      2390     NA     48      4132     33     43
 749     NA     30      2402     NA     41      4135     54     52
 799     NA      7      2426     NA     55      4149     NA     45
 806     42     41      2458     41     39      4157     52     50
 816     55     54      2465     19     49      4165     42     45
 828     NA     33      2466     NA     22      4171     21     25
 842     NA     10      2493     16     36      4186     NA     51
 885     45     47      2499     NA     47      4190     NA     23
 888     NA     18      2501     NA      6      4191     NA     29
 894     NA     18      2514     NA     30      4214     NA     27
 911     20     35      2515     NA     48      4245     56     50
 913     31     43      2537     NA     20      4258     45     46
 914     NA     25      2568     NA      4      4268     NA     17
 942     41     47      2586     NA     55      4276     43     53
 948     NA     52      2595     23     42      4299     NA      9
 961     NA     54      2622     NA     31      4312     51     49
 970     39     26      2625     NA     49      4317     NA     50
 989     21     29      2676     NA      8      4354     NA     45
1005     NA     36      2689     NA     56      4366     NA     12
1020     54     52      2697     NA     12      4368     NA     50
1044     NA     35      2755     NA     13      4379     33     29
1054     NA     48      2793     NA     19      4401     NA     19
1079     17     15      2817     NA     12      4406     NA      4
1086     37     34      2827     NA     13      4408     31     29
1096     41     46      2830     34     24      4410     47     43
1100     52     54      2844     NA     31      4414     NA      5
1150     NA     45      2847     NA     46      4419     NA      5
1156     NA     21      2854     52     49      4491     59     60
1175     NA     41      2907     NA     46      4501     45     42
1201     NA     11      2911     19     36      4551     NA     45
1251     NA     37      2956     NA     37      4577     NA     24
1275     13     63      2963     NA     10      4593     NA     48
1286     NA      7      2964     NA     53      4601     NA     51
1290     NA      0      2968     NA     43      4622     NA     22
1314     50     57      2992     NA     20      4635     45     49
1339     NA     54      3015     13     24      4642     NA     54
1360     NA     52      3059     55     54      4654     NA     10
1363     NA     56      3066     24     33      4673     NA     55
1392     17     33      3079      9     33      4709     NA     46
1409     NA     37      3109     45     49      4718     NA     14
1419     NA      1      3110     55     51      4720     NA     12
1425     NA     35      3120     44     47      4724     51     44
1432     52     51      3135     26     40      4732     55     53
1441     NA     52      3144     NA     44      4734     50     51
1445      6     29      3147     NA     11      4741     NA      9
1449     NA      4      3163     54     52      4761     NA      8
1458     48     49      3176     43     49      4765     NA     41
1476     NA     51      3177     NA     47      4823     NA     10
1480     44     42      3192     NA     52      4843     NA     49
1496     44     48      3193     NA      2      4869     NA     40
1516     NA     57      3198     54     52      4870     NA     54
1531     NA     40      3216     21     34      4905     NA     12
1550     NA     46      3232     NA     21      4924     NA     14
1560     NA      4      3253     NA     59      4936     NA     43
1568     28     41      3256     NA     25      4967     NA     52
1582     NA     24      3269     NA     45      5008     NA     30
1585     NA     36      3283     53     44      5027     12     35
1591     NA     13      3301     NA     50      5051     NA     40
1592     NA     46      3302     NA     36      5064     49     47
1613     NA     11      3306     NA     88      5069     NA     49
1636     NA     50      3310     NA     25      5077     48     46
1638     NA     11      3317     NA     53      5104     NA     36
1640     NA     54      3320     NA     50      5152     54     55
1648     49     43      3330      9     33      5166     20     30
1682     NA     29      3350     45     48      5171     34     43
1702     NA     52      3370     55     54      5185     NA     37
1731     46     50      3386     NA     55      5200     NA     35
1733     28     42      3456     55     52                        

 ID    ORIG    CORR      ID    ORIG    CORR      ID    ORIG    CORR
	R8115.  R8115.          R8115.  R8115.          R8115.  R8115.
------------------      ------------------      ------------------
  10      0      1      1733     21      7      3577     NA      0
  11      7     38      1745      0     14      3587     NA     19
  46     NA     51      1750     NA      3      3588     NA      8
  48     NA     26      1751     NA     19      3602     NA      5
  81     50     24      1777     NA      0      3623     NA     43
  91     NA     34      1785     NA      3      3627     NA      0
 104     NA      0      1810     NA      0      3653     NA     27
 216     35     13      1834     NA     29      3665     NA     27
 220      1      3      1858     NA     40      3670     NA     12
 241     NA      2      1860     NA     23      3672     NA      8
 250     NA      3      1866      0      1      3758     NA      4
 265     NA     25      1893     NA     28      3764      0      3
 288     NA     13      1903     NA      1      3768     13      9
 313     NA      7      1970      0      1      3777     32     28
 326     29      9      1976     24      6      3784     NA      3
 377      0      1      1983     NA      0      3821     NA     35
 381     NA     19      1993     20     10      3849     NA     10
 385     NA     10      2005      0      1      3868     NA      0
 388     NA      0      2015     28     21      3948     NA     23
 401     NA     11      2019     NA      0      3954     NA     30
 415     NA     37      2035     NA     47      3960     NA      2
 438     NA     11      2098     NA      2      3966      6      8
 444     NA      7      2140     NA      5      3998     NA      4
 445     16      5      2166     NA     19      4035      3     10
 478      0      2      2180     NA     23      4074     22     21
 484     NA     13      2228     NA     17      4113     NA     11
 520     NA      1      2234     NA     22      4135      0      2
 532     NA     13      2241     NA     20      4149     NA      6
 553     NA     39      2263     45     22      4165     11      8
 624     NA      9      2287      0      2      4171     31     27
 630     NA     14      2288      9      4      4190     NA     27
 648      0      2      2390     NA      5      4191     NA     16
 658     NA      0      2458     11     13      4214     NA     30
 729     NA      0      2465     69     39      4245      0      6
 749     NA      0      2493     39     19      4258      8      7
 806      0      1      2499     NA      5      4268     NA     35
 828     NA     16      2501     NA     47      4312      1      3
 842     NA      1      2514     NA     24      4317     NA      4
 885      9      7      2515     NA     11      4354     NA     10
 888     NA     34      2537     NA     37      4366     NA     40
 894     NA      4      2568     NA     43      4368     NA      5
 914     NA     13      2595     30      5      4401     NA      0
 942     13      7      2625     NA      3      4405     NA     13
 961     NA      0      2676     NA     48      4406     NA      0
 970     14     27      2697     NA     46      4408     18     23
 989     28     17      2793     NA     34      4410      8     12
1005     NA      9      2817     NA     39      4419     NA     44
1020      0      2      2827     NA     38      4491      1      0
1044     NA     13      2830      0     23      4501      4     NA
1054     NA      2      2844     NA     22      4551     NA      8
1079     39     41      2847     NA      6      4577     NA     31
1086     20     23      2854      1      4      4593     NA      5
1096     10      5      2907     NA      6      4601     NA      5
1150     NA      0      2911     33     16      4622     NA     28
1175     NA      0      2956     NA     15      4635      8      4
1201     NA     35      2963     NA      0      4642     NA      0
1251     NA     13      2968     NA     10      4709     NA      4
1275     74     24      2992     NA     35      4718     NA     38
1286     NA     47      3015     32     21      4720     NA     47
1290     NA     45      3066     28     19      4724      1      8
1314     13      6      3109      8      4      4732      0      2
1339     NA      0      3120     14     11      4734      1      0
1363     NA      0      3135     27     13      4741     NA     38
1392     32     16      3144     NA      8      4761     NA     36
1409     NA     18      3147     NA     41      4765     NA     13
1419     NA      0      3163      0      2      4843     NA      0
1425     NA      7      3176      9      3      4869     NA     13
1445     45     22      3177     NA      4      4924     NA     41
1449     NA     47      3192     NA      0      4936     NA      4
1458      2      1      3193     NA     46      4943     NA     35
1480     12     14      3198      0      2      4967     NA      4
1516     NA      0      3216     33     20      5008     NA     25
1531     NA     13      3232     NA      0      5027     NA      0
1550     NA      8      3256     NA     23      5051     NA      5
1560     NA     51      3269     NA      7      5064      0      1
1568     22      9      3283      0      9      5069      2      4
1582     NA     28      3302     NA     15      5077      4      6
1585     NA     16      3317     NA     14      5090     NA     51
1591     NA      6      3320     NA      0      5104     NA     16
1592     NA      6      3350      7      4      5152      1      0
1636     NA      7      3456      0      3      5166     32     22
1638     NA     44      3462      0      2      5171     18      9
1682     NA     20      3491     NA     16      5185     NA     16
1731      8      4      3547     NA     23      5200     NA     15

 ID   ORIG   CORR       ID    ORIG   CORR      ID    ORIG   CORR
       R8116. R8116.           R8116. R8116.          R8116. R8116.
------------------      ------------------     ------------------
  36      8     12      1751     NA      0     3588     NA      0 
  46     NA      0      1777     NA     31     3602     NA     22 
  48     NA      4      1785     NA     22     3623     NA      0 
  87      4      6      1810     NA     32     3627     NA     47 
  91     NA      0      1834     NA      0     3653     NA      0 
 104     NA     51      1858     NA      0     3656     26      0 
 241     NA     28      1860     NA      0     3665     NA      0 
 250     NA      2      1868      0     10     3670     NA      3 
 265     NA      0      1893     NA      0     3672     NA      0 
 288     NA      0      1903     NA      7     3758     NA     19 
 313     NA      0      1983     NA     40     3777      0      1 
 341      0      1      2009     21      0     3784     NA     16 
 381     NA      8      2019     NA      0     3821     NA      0 
 385     NA      1      2035     NA      0     3849     NA      1 
 388     NA     11      2036      0      5     3868     NA      3 
 401     NA      0      2098     NA      2     3922     NA      0 
 415     NA      1      2140     NA      0     3931      1      2 
 438     NA     12      2166     NA      0     3948     NA      0 
 444     NA      5      2180     NA      0     3954     NA      0 
 458      0      1      2202     20      0     3960     NA      4 
 484     NA      0      2224      0      1     3998     NA      0 
 520     NA     22      2228     NA     18     4100     NA      0 
 532     NA      0      2234     NA      0     4113     NA      9 
 553     NA      0      2241     NA      0     4119      9      0 
 624     NA      2      2250      0      1     4132     19      9 
 630     NA      0      2390     NA      0     4149     NA      0 
 658     NA      0      2499     NA      0     4157      0      2 
 729     NA     34      2501     NA      0     4186     NA      0 
 749     NA     22      2514     NA      0     4190     NA      0 
 816      0      1      2515     NA      0     4191     NA     11 
 828     NA      0      2537     NA     40     4214     NA      0 
 842     NA     42      2568     NA      0     4268     NA      0 
 888     NA      3      2586     NA      0     4276     10      0 
 894     NA     27      2595      0      6     4317     NA      0 
 913     12      0      2625     NA      0     4354     NA      0 
 914     NA     15      2676     NA      0     4366     NA      0 
 961     NA      0      2689     NA      0     4368     NA      0 
 989      3      6      2697     NA      0     4401     NA     31 
1005     NA      7      2793     NA      0     4406     NA     50 
1044     NA     10      2817     NA      0     4408      3      0 
1054     NA      4      2827     NA      0     4419     NA      0 
1100      3      1      2830     24     11     4501      0     NA 
1136     NA      0      2844     NA      0     4551     NA      0 
1150     NA     11      2847     NA      6     4577     NA      0 
1175     NA     14      2907     NA      3     4593     NA      0 
1201     NA      4      2956     NA      0     4601     NA      0 
1251     NA      0      2963     NA     44     4622     NA      0 
1286     NA      0      2968     NA      0     4642     NA      0 
1290     NA     46      2992     NA      0     4673     NA      0 
1339     NA      0      3059      0      1     4709     NA      6 
1363     NA      0      3079     24      0     4718     NA      0 
1409     NA      0      3110      0      4     4720     NA      0 
1419     NA     54      3144     NA      0     4741     NA      0 
1425     NA      9      3147     NA      0     4761     NA      7 
1432      0      1      3177     NA      2     4765     NA      0 
1449     NA      0      3192     NA      3     4843     NA      3 
1476     NA      0      3193     NA      0     4869     NA      0 
1496      4      0      3232     NA     31     4924     NA      0 
1516     NA      4      3256     NA      0     4936     NA      2 
1531     NA      0      3269     NA      0     4943     NA      0 
1550     NA      7      3301     NA      0     4967     NA      3 
1560     NA      0      3302     NA      0     5008     NA      2 
1582     NA      0      3306     NA      0     5027     NA     17 
1585     NA      0      3317     NA     21     5051     NA     10 
1591     NA     32      3320     NA      3     5064      2      3 
1592     NA      0      3330     24      0     5104     NA      0 
1636     NA      0      3370      0      1     5185     NA      0 
1638     NA      0      3491     NA      4     5200     NA      0 
1640     NA      0      3508     26     24                        
1648      6     12      3547     NA      0 
1682     NA      4      3577     NA     22 
1750     NA      0      3587     NA      0

The NLS Investigator contains the most recent release of each NLS cohort. Known problems are found below. For further questions, please contact NLS User Services.

TOTAL NET FAMILY INCOME and TOTAL NET FAMILY ASSETS variables updated

Most Recent Errata posted on 08/16/2017

New summation variables--TOTAL NET FAMILY INCOME and TOTAL NET FAMILY ASSETS--have been constructed for the NLS Older Men's Cohort. This was done to correct inconsistencies across rounds in the treatment of noninterviewed respondents. This information has been updated in the Older Men data.

Errata sheet for the NLS of Older Men (1966-1990)

Revised: 06/1992

Questionnaires for the Young Men's cohort are available for all survey years from 1966 to 1981. Click a link to view the corresponding file.

• 1966 | Young Men's Questionnaire

• 1967 | Young Men's Questionnaire

• 1968 | Young Men's Questionnaire

• 1969 | Young Men's Questionnaire

• 1970 | Young Men's Questionnaire

• 1971 | Young Men's Questionnaire

• 1973 | Young Men's Questionnaire

• 1975 | Young Men's Questionnaire

• 1976 | Young Men's Questionnaire

• 1978 | Young Men's Questionnaire

• 1980 | Young Men's Questionnaire

• 1981 | Young Men's Questionnaire

Questionnaires for the Older Men's cohort are available for all survey years from 1966 to 1990. Click a link to view the corresponding file.

• 1966 | Older Men's Questionnaire

• 1967 | Older Men's Questionnaire

• 1968 | Older Men's Questionnaire

• 1969 | Older Men's Questionnaire

• 1971 | Older Men's Questionnaire

• 1973 | Older Men's Questionnaire

• 1975 | Older Men's Questionnaire

• 1976 | Older Men's Questionnaire

• 1978 | Older Men's Questionnaire

• 1980 | Older Men's Questionnaire

• 1981 | Older Men's Questionnaire

• 1983 | Older Men's Questionnaire

• 1990 | Older Men's Questionnaire Note: This file also includes 1990 Widow's Questionnaire.