R: Labour Force Participation of Married Women 1967-1971

Heckman {vcdExtra} | R Documentation

## Labour Force Participation of Married Women 1967-1971

### Description

1583 married women were surveyed over the years 1967-1971, recording whether or not they were employed in the labor force.

The data, originally from Heckman & Willis (1977) provide an example of modeling longitudinal categorical data, e.g., with markov chain models for dependence over time.

### Usage

    data(Heckman)

### Format

A 5-dimensional array resulting from cross-tabulating 5 variables for 1583 observations. The variable names and their levels are:

No | Name | Levels
1 | `e1971` | `"71Yes", "No"`
2 | `e1970` | `"70Yes", "No"`
3 | `e1969` | `"69Yes", "No"`
4 | `e1968` | `"68Yes", "No"`
5 | `e1967` | `"67Yes", "No"`

### Details

Lindsey (1993) fits an initial set of logistic regression models examining the dependence of employment in 1971 (`e1971`) on successive subsets of the previous years, `e1970`, `e1969`, ... `e1967`.

Alternatively, one can examine markov chain models of first-order (dependence on previous year), second-order (dependence on previous two years), etc.

### Source

Lindsey, J. K. (1993). Models for Repeated Measurements Oxford, UK: Oxford University Press, p. 185.

### References

Heckman, J.J. & Willis, R.J. (1977). "A beta-logistic model for the analysis of sequential labor force participation by married women." Journal of Political Economy, 85: 27-58

### Examples

    data(Heckman)

    # independence model
    mosaic(Heckman, shade=TRUE)
    # same, as a loglm()
    require(MASS)
    (heckman.mod0 <- loglm(~ e1971+e1970+e1969+e1968+e1967, data=Heckman))
    mosaic(heckman.mod0, main="Independence model")

    # first-order markov chain: bad fit
    (heckman.mod1 <- loglm(~ e1971*e1970 + e1970*e1969 +e1969*e1968 + e1968*e1967, data=Heckman))
    mosaic(heckman.mod1, main="1st order markov chain model")

    # second-order markov chain: bad fit
    (heckman.mod2 <- loglm(~ e1971*e1970*e1969 + e1970*e1969*e1968 +e1969*e1968*e1967, data=Heckman))
    mosaic(heckman.mod2, main="2nd order markov chain model")

    # third-order markov chain: fits OK
    (heckman.mod3 <- loglm(~ e1971*e1970*e1969*e1968 + e1970*e1969*e1968*e1967, data=Heckman))
    mosaic(heckman.mod2, main="3rd order markov chain model")

[Package vcdExtra version 0.7-1 Index]