Multiple Linear Regression (MLR) Example in R

Load the lavaan package at the beginning of the session

library(lavaan)
## Warning: package 'lavaan' was built under R version 3.1.3
## This is lavaan 0.5-18
## lavaan is BETA software! Please report any bugs.

The data file is read in, columns are named, and missing values are specified.

dat <- read.csv("../../data/job_placement.csv", header = FALSE)
colnames(dat) <- c("id", "wjcalc", "wjspl", "wratspl", "wratcalc", "waiscalc", "waisspl", "edlevel", "newschl", "suspend", "expelled", "haveld", "female", "age")
dat[dat == 99999] <- NA

This builds the model object.

MLRModel <- "wjspl ~ edlevel + newschl + suspend + expelled +
             haveld + female + age
             wjspl ~ 1
             "

This fits the model and returns an output summary.

output <- sem(model = MLRModel, data = dat)
summary(output)
## lavaan (0.5-18) converged normally after   1 iterations
## 
##                                                   Used       Total
##   Number of observations                           313         322
## 
##   Estimator                                         ML
##   Minimum Function Test Statistic                0.000
##   Degrees of freedom                                 0
## 
## Parameter estimates:
## 
##   Information                                 Expected
##   Standard Errors                             Standard
## 
##                    Estimate  Std.err  Z-value  P(>|z|)
## Regressions:
##   wjspl ~
##     edlevel           1.162    0.324    3.584    0.000
##     newschl           0.063    0.747    0.085    0.932
##     suspend          -0.052    0.773   -0.067    0.947
##     expelled         -2.758    1.098   -2.510    0.012
##     haveld           -6.974    0.987   -7.063    0.000
##     female            0.720    0.792    0.909    0.363
##     age               0.412    0.207    1.994    0.046
## 
## Intercepts:
##     wjspl            21.953    4.414    4.974    0.000
## 
## Variances:
##     wjspl            39.904    3.190