Demo.twolevel: Demo dataset for a illustrating a multilevel CFA.

Description Usage Format Examples

Description

A toy dataset containing measures on 6 items (y1-y6), 3 within-level covariates (x1-x3) and 2 between-level covariates (w1-w2). The data is clustered (200 clusters of size 5, 10, 15 and 20), and the cluster variable is “cluster”.

Usage

1

Format

A data frame of 2500 observations of 12 variables. clusters.

y1

item 1

y2

item 2

y3

item 3

y4

item 4

y5

item 5

y6

item 6

x1

within-level covariate 1

x2

within-level covariate 2

x3

within-level covariate 3

w1

between-level covariate 1

w2

between-level covariate 2

cluster

cluster variable

Examples

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head(Demo.twolevel)

model <- '
    level: 1
        fw =~ y1 + y2 + y3
        fw ~ x1 + x2 + x3
    level: 2
        fb =~ y1 + y2 + y3
        fb ~ w1 + w2
'
fit <- sem(model, data = Demo.twolevel, cluster = "cluster")
summary(fit)

Example output

This is lavaan 0.6-3
lavaan is BETA software! Please report any bugs.
          y1         y2         y3         y4         y5         y6         x1
1  0.2293216  1.3555232 -0.6911702  0.8028079 -0.3011085 -1.7260671  1.1739003
2  0.3085801 -1.8624397 -2.4179783  0.7659289  1.6750617  1.1764210 -1.0039958
3  0.2004934 -1.3400514  0.4376087  1.1974194  1.1951594  1.4988962 -0.4402545
4  1.0447982 -0.9624490 -0.4464898 -0.2027252 -0.4590574  1.1734061 -0.6253657
5  0.6881792 -0.4565633 -0.6422296  0.9900408  1.7662535  0.7944601 -0.8450025
6 -2.0687644 -0.5997856  0.3148418  0.6764432 -0.6519928  1.8405605 -0.7831784
           x2         x3         w1         w2 cluster
1 -0.62315173  0.6470414 -0.2479975 -0.4989800       1
2 -0.56689380  0.0201264 -0.2479975 -0.4989800       1
3 -2.13432572 -0.4591246 -0.2479975 -0.4989800       1
4 -0.33688869  1.2852093 -0.2479975 -0.4989800       1
5 -0.04229954  1.5598970 -0.2479975 -0.4989800       1
6 -0.22441996 -0.3814231 -2.3219338 -0.6910567       2
lavaan 0.6-3 ended normally after 36 iterations

  Optimization method                           NLMINB
  Number of free parameters                         20

  Number of observations                          2500
  Number of clusters [cluster]                     200

  Estimator                                         ML
  Model Fit Test Statistic                       8.092
  Degrees of freedom                                10
  P-value (Chi-square)                           0.620

Parameter Estimates:

  Information                                 Observed
  Observed information based on                Hessian
  Standard Errors                             Standard


Level 1 [within]:

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)
  fw =~                                               
    y1                1.000                           
    y2                0.774    0.034   22.671    0.000
    y3                0.734    0.033   22.355    0.000

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)
  fw ~                                                
    x1                0.510    0.023   22.037    0.000
    x2                0.407    0.022   18.273    0.000
    x3                0.205    0.021    9.740    0.000

Intercepts:
                   Estimate  Std.Err  z-value  P(>|z|)
   .y1                0.000                           
   .y2                0.000                           
   .y3                0.000                           
   .fw                0.000                           

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)
   .y1                0.986    0.046   21.591    0.000
   .y2                1.066    0.039   27.271    0.000
   .y3                1.011    0.037   27.662    0.000
   .fw                0.546    0.040   13.539    0.000


Level 2 [cluster]:

Latent Variables:
                   Estimate  Std.Err  z-value  P(>|z|)
  fb =~                                               
    y1                1.000                           
    y2                0.717    0.052   13.824    0.000
    y3                0.587    0.048   12.329    0.000

Regressions:
                   Estimate  Std.Err  z-value  P(>|z|)
  fb ~                                                
    w1                0.165    0.079    2.093    0.036
    w2                0.131    0.076    1.715    0.086

Intercepts:
                   Estimate  Std.Err  z-value  P(>|z|)
   .y1                0.024    0.075    0.327    0.743
   .y2               -0.016    0.060   -0.269    0.788
   .y3               -0.042    0.054   -0.777    0.437
   .fb                0.000                           

Variances:
                   Estimate  Std.Err  z-value  P(>|z|)
   .y1                0.058    0.047    1.213    0.225
   .y2                0.120    0.031    3.825    0.000
   .y3                0.149    0.028    5.319    0.000
   .fb                0.899    0.118    7.592    0.000

lavaan documentation built on March 10, 2021, 5:05 p.m.

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