Chapter 3: Guide to the Mature Women Data (continued)

Table of Contents

3.3 Mature Women Codebook System

All variables present on a main file data set are documented via: (1) a cohort-specific codebook, (2) an accompanying codebook supplement, and (3) error updates. This section describes these three primary components of the codebook system and discusses the important types of information found within each.

Codebooks

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 using the NLS Investigator at www.nlsinfo.org/investigator by clicking on a variable's reference number once a list of variables has been selected.

This feature allows researchers to customize their documentation for their particular research needs and to select and print information for variables of interest to them.

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. Users will find that Mature Women CAPI codeblocks present greater detail on each variable, including question text, universe totals, universe skip patterns, and additional range of acceptable values information (some of this information was also added to PAPI codeblocks as time permitted). Each of these terms is described in more detail below.

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 relating to the interview in the early survey years.

Codebook Item Descriptions

The following common types of information for each variable within a codeblock will be described in this section: coding information, multiple responses, missing responses, derivations, frequency distributions, questionnaire items (question numbers), universe information, valid values ranges, and verbatims. The sample codeblocks in Figures 3.3.1 and 3.3.2 provide visual examples of this information. The first codeblock is a created variable and the second is a question actually asked of respondents during the interview, allowing users to identify the differences between codeblocks for these two types of variables.

Figure 3.3.1 Sample Created Variable Codeblock

Figure 3.3.2 Sample Interview Question Codeblock

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 for a given variable in the NLS codeblock 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 or yes/no variables are uniformly coded "Yes" = 1, "No" = 0. Other dichotomous variables have frequently been reformulated to permit this convention to be followed.

Discrete (Categorical), as in the case of 'Activity Most of Survey Week 92.'

Continuous (Quantitative), as in the case of 'Hourly Rate of Pay at Current or Last Job 81 *KEY*.' These variables have continuous data, but the codebook presents a frequency distribution as in the sample codeblocks above for ease of use.

Combined Quantitative-Qualitative Variables, i.e., variables that are ostensibly quantitative but may have nonquantitative (categorical) responses, utilize integers equaling the actual values for the quantitative responses and 999 for the qualitative (categorical) response.  For example, "YEAR STOPPED WORKING AT 1ST MOST RECENT JOB INTRVNG & LAST 73" is coded as follows:

60 thru 73  actual year
999    still working there

Multiple Responses: Response categories to multiple entry questions found in certain job search, child care, discrimination, or health questions have been coded in a geometric progression. For example, more than one response to the question "Method of seeking employment to be used in next year" was possible. The response categories to that question were each assigned a value as follows:

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. (Staff are working on providing unpacked versions of these variables; see Appendix C for more information.)

Missing Responses: Negative numbers are used to indicate that a respondent does not have a valid value for a particular variable. Different numbers indicate different reasons for nonresponse:

• "Refusal" indicates that the respondent refused to answer a given question. These respondents are assigned a value of -1. This code is used for all interviews of this cohort.
• "Don't know" indicates that the respondent did not know the answer to a given question. These respondents are assigned a value of -2. This code is used for all interviews of this cohort.
• "Invalid skip" indicates that the respondent was not asked a question that she should have answered, usually due to programming or interviewer error. These respondents are assigned a value of -3. This code is only used consistently for CAPI interviews (1995-2003).
• "Valid skip" has slightly different meanings depending on survey year. In CAPI interviews (1995-2003), this code indicates that the respondent was skipped past the question intentionally, because she was not in the universe of respondents to whom that question applied. These respondents are assigned a value of -4. In PAPI interviews (1967-92), this code indicates either that the respondent is not in the applicable universe or there was some other error that resulted in a missing response (which generally would have resulted in an invalid skip code in a CAPI survey).
• Finally, a "noninterview" value of -5 indicates that a respondent was not interviewed in that survey year. This code is used for all interviews of this cohort.

Three additional negative codes are used only with the NLS women's cohorts for particular types of nonresponse:

• In questions dealing with usual hours per week worked, if the respondent reported that her hours varied, she was assigned a code of -6.
• Women who had been widowed since the last survey were asked a series of questions regarding their husband's care and their financial situation since his death. A code of -7 was assigned to women whom the interviewer judged to be emotionally unable to answer these questions.
• Some variables in multiple response question series included codes of -8, indicating that the respondent was done with the series.

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 for their needs. In the 'Hourly Rate of Pay at Current or Last Job 81 *KEY*' example (Figure 3.3.1), the derivation describes in detail the items of the interview schedule used to create the variable. If the derivation is too lengthy to include in the codebook, the codeblock will instead refer users to the supplemental documentation item that contains variable creation information.

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 the illustrative variables in Figures 3.3.1 and 3.3.2, the frequency count is straightforward. For example, in Figure 3.3.1 there are twelve categories; the maximum category shown is 1000 and above (since two decimal places are implied, 1000 represents $10.00), for which there is a frequency count of 143.

Questionnaire Item: "Questionnaire item" is a generic term identifying the 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. Questionnaire item identifications are located in the extreme right hand column of the codebook. The question number, when available, is copied exactly from the questionnaire. The question numbering system is described in the questionnaire section earlier in this chapter. In Figure 3.3.2, the question number is RSP-81I-ARR-01.

During PAPI interview years, all created variables have a question name of simply "CV." Created variables  in CAPI survey years usually include the letters CV in the question name and usually have the word *KEY* in their title.

Valid Values Range: Depicted below the frequency distribution are the maximum and minimum fields, which define the range of valid values (the upper and lower limits) for a given question. "MINIMUM" indicates the smallest recorded value exclusive of nonresponse codes; "MAXIMUM" indicates the largest recorded value. In the case of the 'Hourly Rate of Pay at Current or Last Job' example (Figure 3.3.1), the maximum, or highest value recorded, is 2500 with two implied decimal places, or $25.00.

Topcoding Income and Asset Values: Confidentiality issues restrict release of all income and asset values. To ensure 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, as do the set maximum values. From 1967 through 1972, upper limit dollar amounts were set to 999999. From 1974 through 1980, upper limit variables were set to maximum values of 50000, and from 1981 to 1984 the set maximum value was 50001. Beginning in 1986, income amounts exceeding $100,000 were converted to a set maximum value of 100001.

From the cohort's inception, asset variables exceeding upper limits were truncated to 999999. Beginning in 1977, assets exceeding one million were converted to a set maximum value of 999997. Starting in 1992, the Census Bureau also topcoded selected asset items if it considered that the 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 the Codebook Supplement. Information provided within these documents is not available in the electronic documentation files on the NLS CD-ROMs or via download. The following attachments and appendices are included in the Codebook Supplement (PDF).

Attachment 2: 1960, 1980 & 1990 Census of Population Industry and Occupational Classification Codes provides the occupation-industry coding assignments made by Census Bureau personnel from the verbal descriptions obtained in the interviews. Users should refer to the "Industries" or "Occupations & Occupational Prestige Indices" sections in chapter 4 of this guide for information about which coding schemes were used in various survey years. This attachment also contains a copy of the Duncan Socioeconomic Index, an ordinal prestige scale assigning a rank of 0-97 to each of the three digit 1960 Census occupations. (2000 Census codes can be found at www.census.gov.)

Attachment 4: Bose Index provides a mean occupational prestige score for each of the three-digit 1960 occupation codes for respondents of the cohort.

Attachment 5: Employment Status Recodes describes the methodology used by Census to calculate each respondent's employment status from the CPS questions that are asked in each NLS round. This document provides (1) definitions of 'working,' 'with a job but not at work,' 'unemployed,' and 'not in the labor force'; (2) the decision rules used to assign or recode respondents to a particular labor force status; and (3) Census methodology for dealing with exceptions to the rules.

Appendix 3: State Names and State Codes by Census Division Listing
Appendix 4: Derivations for R02847.00 (Reason Left Current Job 1967)
Appendix 5: Source for Occupational Atypicality Codes
Appendix 6: Derivations for R02872.50 (Occupational Training 1967-1972)
Appendix 7: Derivations for R00792.50 (Training prior to 1972)
Appendix 8: Derivations for R00744.05 (Number of Years Worked before 1967 in Occupation)
Appendix 9: Derivations for 1977 *KEY* Variables
Appendix 10: New Geographical and Environmental Variables for the Mature Women's Cohort, 1967-1977
Appendix 11: Derivations for 1971 *KEY* Variables
Appendix 12: Derivations for 1972 *KEY* Variables
Appendix 18: Union Categories - Copy of Coding Instructions for Name of Union or Employee Association
Appendix 19: Derivations for 1982 *KEY* Variables
Appendix 20: Derivations for 1987 *KEY* Variables
Appendix 21: Derivations for 1989 *KEY* Variables
Appendix 22: Derivations for 1992 *KEY* Variables
Appendix 23: Geometric Progression Coding
Appendix 24: Pension Plan Data Documentation
Appendix 36: Summary of the Major Differences between the 1995 and Earlier Surveys
Appendix 37: Summary of 1995 Data Cleaning Issues
Appendix 38: Derivations for 1995 *KEY* and other Created Variables
Appendix 39: Summary of 1997 Data Cleaning Issues
Appendix 40: Derivations for 1997 *KEY* and Other Created Variables
Appendix 41: Derivations for 1999 *KEY* and Other Created Variable
Appendix 42: Derivations for 2001 *KEY* and Other Created Variables
Appendix 43: Derivations for 2003 *KEY* and Other Created Variables
Appendix 44: Variables Used For Matching Mother/Daughter Pairs in the NLS

Error Updates

Prior to working with an NLS data file, users should make every effort to acquire current information on data and/or documentation errors.A variety of methods are used to notify users of errors in the data files and/or documentation and to provide those persons who acquired an NLS data set from CHRR with corrected information. Errors discovered after the release of a data file are distributed in hard copy form to current disc purchasers along with the data set. Error notices also appear, along with information on how to acquire the corrected data and/or documentation, in NLS News, the quarterly newsletter.  An errata sheet may also be accessed on the BLS Web site at www.bls.gov/nls.

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3.4 Data File Search Functions

Variables can be accessed through NLS Investigator, the search and extraction program available at www.nlsinfo.org/investigator. The Investigator provides users with bridging information to the codebook and/or survey instruments. The Investigator search indexes and lists described below can be used individually or combined to produce a more refined list of variables. This section provides only a cursory overview.  Researchers who need more information on the search and extraction process should refer to the Investigator Guide.

Word in Title. The "Word in Title" function allows the user to search for and select those variables whose titles contain any single word or combination of words found in the entire documentation database. This function allows users to easily access variables on a variety of topics but is still dependent on the wording of each variable title. For more information on the naming of variables, see the "Variable Titles" discussion in section 3.2, especially the User Notes.

Area of interest. Areas of interest contain lists of variables grouped by topic. For example, questions on a respondent's health and medical insurance are grouped in the "Health" area of interest. Individual questions may appear in more than one area of interest.

Question name. The data file contains a searchable list of the question numbers for every Mature Women variable. By accessing this list, users who know the question number for the item of interest can locate the variable without performing an "any word" search. Researchers can also browse through the questions for a given questionnaire section.

Reference number. The data file also contains a searchable list of all Mature Women reference numbers. By using this list, researchers can locate variables for which they already know the reference number or they can browse through questions of interest, which are generally arranged in the order in which they were asked during the interview.

Survey Year. Investigator includes an option by which users can limit their searches to a single year of interest. Researchers can browse through all the variables relating to a given survey year (recommended for PAPI years only) or can combine the year with another search to locate specific variables of interest.

Question text/Codebook. These search functions allow users to search for any word or term that appears in the text of a question or anywhere on the codebook page. This allows users to search not just variable titles but also question text, words in frequency distributions, archivist notes, and so on.