R: Total, Direct, and Indirect Effects for Structural Equation...

effects.sem {sem} | R Documentation

## Total, Direct, and Indirect Effects for Structural Equation Models

### Description

The `sem` method for the standard generic function `effects` computes total, direct, and indirect effects for a fitted structural equation model according to the method described in Fox (1980).

### Usage

    ## S3 method for class 'sem'
    effects(object, ...)
    ## S3 method for class 'msem'
    effects(object, ...)

    ## S3 method for class 'semeffects'
    print(x, digits = getOption("digits"), ...)
    ## S3 method for class 'semeffectsList'
    print(x, digits = getOption("digits"), ...)

### Arguments

`object` | a fitted structural-equation model object produced by the `sem` function.
`x` | an object of class `semeffects` or `semeffectsList`, produced by `effects`.
`digits` | digits to print.
`...` | not used.

### Value

`effect.sem` returns an object of class `semeffects` with `Total`, `Direct`, and `Indirect` elements.

### Author(s)

John Fox jfox@mcmaster.ca

### References

Fox, J. (1980) Effect analysis in structural equation models: Extensions and simplified methods of computation. Sociological Methods and Research 9, 3–28.

### See Also

`sem`

### Examples

        ## Not run:

    # These examples are from Fox (1980)

    # In the first pair of examples, readMoments() and specifyModel() read from the
    # input stream. These examples cannot be executed via example() but can be entered
    # at the command prompt. The Blau and Duncan example is repeated using file input;
    # this example can be executed via example().

    # The recursive Blau and Duncan basic stratification model:
    #  x1 is father's education, x2 father's SES, y3 respondent's education,
    #  y4 SES of respondent's first job, y5 respondent's SES in 1962

    R.bd <- readMoments(names=c("x1", "x2", "y3", "y4", "y5"))
    1
    .516 1
    .453 .438 1
    .332 .417 .538 1
    .322 .405 .596 .541 1

    mod.bd <- specifyModel()
    y3 <- x1, gam31
    y3 <- x2, gam32
    y4 <- x2, gam42
    y4 <- y3, beta43
    y5 <- x2, gam52
    y5 <- y3, beta53
    y5 <- y4, beta54

    sem.bd <- sem(mod.bd, R.bd, N=20700, fixed.x=c("x1", "x2"))
    summary(sem.bd)
    effects(sem.bd)

    # The nonrecursive Duncan, Haller, and Portes peer-influences model for observed variables:

    R.DHP <- readMoments(diag=FALSE, names=c("ROccAsp", "REdAsp", "FOccAsp",
    "FEdAsp", "RParAsp", "RIQ", "RSES", "FSES", "FIQ", "FParAsp"))
    .6247
    .3269  .3669
    .4216  .3275  .6404
    .2137  .2742  .1124  .0839
    .4105  .4043  .2903  .2598  .1839
    .3240  .4047  .3054  .2786  .0489  .2220
    .2930  .2407  .4105  .3607  .0186  .1861  .2707
    .2995  .2863  .5191  .5007  .0782  .3355  .2302  .2950
    .0760  .0702  .2784  .1988  .1147  .1021  .0931 -.0438  .2087

    model.dhp <- specifyModel()
    RIQ      -> ROccAsp, gam51,  NA
    RSES     -> ROccAsp, gam52,  NA
    FSES     -> FOccAsp, gam63,  NA
    FIQ      -> FOccAsp, gam64,  NA
    FOccAsp  -> ROccAsp, beta56, NA
    ROccAsp  -> FOccAsp, beta65, NA
    ROccAsp <-> ROccAsp, ps55,   NA
    FOccAsp <-> FOccAsp, ps66,   NA
    ROccAsp <-> FOccAsp, ps56,   NA

    # Note: The following generates a warning because not all of the variables
    #       in the correlation matrix are used
    sem.dhp <- sem(model.dhp, R.DHP, 329,
                    fixed.x=c('RIQ', 'RSES', 'FSES', 'FIQ'))
    summary(sem.dhp)
    effects(sem.dhp)

    ## End(Not run)

    ## the following example may be executed via example()

    etc <- system.file(package="sem", "etc") # path to data and model files

    # The recursive Blau and Duncan basic stratification model:
    #  x1 is father's education, x2 father's SES, y3 respondent's education,
    #  y4 SES of respondent's first job, y5 respondent's SES in 1962

    (R.bd <- readMoments(file=file.path(etc, "R-Blau-Duncan.txt"),
    					names=c("x1", "x2", "y3", "y4", "y5")))
    (mod.bd <- specifyModel(file=file.path(etc, "model-Blau-Duncan.txt")))
    sem.bd <- sem(mod.bd, R.bd, N=20700, fixed.x=c("x1", "x2"))
    summary(sem.bd)
    effects(sem.bd)

[Package sem version 3.1-13 Index]