A data set containing data on work, salary, and education from the 2014 General Social Survey. Missing data are explicitly identified with NAs and all data are represented as factors when appropriate.

data(gss14)

Format

A data frame with 2538 rows and 19 variables:

YEAR

GSS year for this respondent

INCOME06

Total family income (2006 version)

INCOM16

Rs family income when 16 yrs old

REG16

Region of residence, age 16

RACE

Race of respondent

SEX

Respondents sex

SPDEG

Spouses highest degree

MADEG

Mothers highest degree

PADEG

Fathers highest degree

DEGREE

Rs highest degree

CHILDS

Number of children

SPWRKSLF

Spouse self-emp. or works for somebody

SPHRS1

Number of hrs spouse worked last week

MARITAL

Marital status

WRKSLF

R self-emp or works for somebody

HRS1

Number of hours worked last week

WRKSTAT

Labor force status

ID_

Respondent id number

BALLOT

Ballot used for interview

Source

https://gssdataexplorer.norc.org

Examples

str(gss14)
#> 'data.frame':	2538 obs. of  19 variables:
#>  $ YEAR    : int  2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 ...
#>  $ INCOME06: Factor w/ 25 levels "Under $1 000",..: 21 25 18 25 NA 25 NA 21 11 22 ...
#>  $ INCOM16 : Factor w/ 5 levels "Far below average",..: 2 3 2 2 4 4 2 3 3 1 ...
#>  $ REG16   : Factor w/ 10 levels "Foreign","New england",..: 3 3 2 3 3 2 3 10 3 3 ...
#>  $ RACE    : Factor w/ 3 levels "White","Black",..: 1 1 1 1 1 1 1 1 1 3 ...
#>  $ SEX     : Factor w/ 2 levels "Male","Female": 1 2 1 2 2 2 1 1 2 2 ...
#>  $ SPDEG   : Factor w/ 6 levels "-1","Lt high school",..: NA 5 NA 5 3 4 2 6 NA 3 ...
#>  $ MADEG   : Factor w/ 5 levels "Lt high school",..: 1 3 2 2 5 2 NA 2 1 1 ...
#>  $ PADEG   : Factor w/ 5 levels "Lt high school",..: NA 4 NA 2 1 4 1 2 NA NA ...
#>  $ DEGREE  : Factor w/ 5 levels "Lt high school",..: 4 4 2 4 4 4 2 5 1 3 ...
#>  $ CHILDS  : Factor w/ 9 levels "0","1","2","3",..: 1 1 2 3 4 2 3 3 5 4 ...
#>  $ SPWRKSLF: Factor w/ 2 levels "Self-employed",..: NA 2 NA 2 2 1 NA 2 NA 2 ...
#>  $ SPHRS1  : int  NA 75 NA 40 NA 60 NA 60 NA 60 ...
#>  $ MARITAL : Factor w/ 5 levels "Married","Widowed",..: 3 1 3 1 1 1 1 1 5 1 ...
#>  $ WRKSLF  : Factor w/ 2 levels "Self-employed",..: 1 2 2 2 2 1 NA 2 NA 2 ...
#>  $ HRS1    : int  60 40 NA 20 NA 60 NA 40 NA 55 ...
#>  $ WRKSTAT : Factor w/ 8 levels "Working fulltime",..: 1 1 4 2 5 1 NA 1 8 1 ...
#>  $ ID_     : int  1 2 3 4 5 6 7 8 9 10 ...
#>  $ BALLOT  : Factor w/ 3 levels "Ballot a","Ballot b",..: 3 3 1 2 3 1 2 2 3 3 ...
head(gss14)
#>   YEAR         INCOME06       INCOM16           REG16  RACE    SEX
#> 1 2014 $75000 to $89999 Below average Middle atlantic White   Male
#> 2 2014  $150000 or over       Average Middle atlantic White Female
#> 3 2014  $40000 to 49999 Below average     New england White   Male
#> 4 2014  $150000 or over Below average Middle atlantic White Female
#> 5 2014             <NA> Above average Middle atlantic White Female
#> 6 2014  $150000 or over Above average     New england White Female
#>            SPDEG          MADEG          PADEG      DEGREE CHILDS      SPWRKSLF
#> 1           <NA> Lt high school           <NA>    Bachelor      0          <NA>
#> 2       Bachelor Junior college       Bachelor    Bachelor      0  Someone else
#> 3           <NA>    High school           <NA> High school      1          <NA>
#> 4       Bachelor    High school    High school    Bachelor      2  Someone else
#> 5    High school       Graduate Lt high school    Bachelor      3  Someone else
#> 6 Junior college    High school       Bachelor    Bachelor      1 Self-employed
#>   SPHRS1  MARITAL        WRKSLF HRS1          WRKSTAT ID_   BALLOT
#> 1     NA Divorced Self-employed   60 Working fulltime   1 Ballot c
#> 2     75  Married  Someone else   40 Working fulltime   2 Ballot c
#> 3     NA Divorced  Someone else   NA Unempl, laid off   3 Ballot a
#> 4     40  Married  Someone else   20 Working parttime   4 Ballot b
#> 5     NA  Married  Someone else   NA          Retired   5 Ballot c
#> 6     60  Married Self-employed   60 Working fulltime   6 Ballot a