Compact one-line or table summary printed to the console.
Arguments
- x
A
tseLCAobject returned bythree_step().- ...
Further arguments.
- digits
Integer. Number of decimal places for coefficient tables.
Examples
d <- generate_data(100, "high", "covariate", seed = 1)
fit_m <- three_step(d, paste0("Y", 1:6), n_classes = 3)
print(fit_m)
#> tseLCA -- measurement model
#> Classes: 3 Log-lik: -295.0095 AIC: 630.02 BIC: 682.12
#> Entropy R²: 0.8683
# \donttest{
d <- generate_data(200, "high", "covariate", seed = 1)
fit <- three_step(d, paste0("Y", 1:6), n_classes = 3,
Zp.names = "Zp", use.simple.cov = TRUE)
print(fit)
#> tseLCA -- three-step covariate model
#> Classes: 3 Estimator: ML Log-lik: -548.6403 AIC: 1177.28 BIC: 1309.21
#> Entropy R² (covariate-adjusted): 0.8589
#>
#> Covariate coefficients (three-step):
#> Estimate Std.Error z.value p.value
#> Intercept:C2 2.2334 0.6258 3.5688 < 0.001 ***
#> Zp:C2 -1.1570 0.3002 -3.8545 < 0.001 ***
#> Intercept:C3 -3.2742 0.7191 -4.5529 < 0.001 ***
#> Zp:C3 0.9401 0.1896 4.9587 < 0.001 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# }
# \donttest{
d <- generate_data(200, "high", "distal", seed = 2)
fit <- three_step(d, paste0("Y", 1:6), n_classes = 3,
Zo.name = "Zo", use.simple.cov = TRUE)
print(fit)
#> tseLCA -- three-step distal outcome model
#> Classes: 3 Estimator: ML Family: gaussian
#> Log-lik: -892.7558 AIC: 1831.51 BIC: 1907.37
#>
#> Distal outcome means by class:
#> Estimate Std.Error z.value p.value
#> mu_C1 (mean) -0.8223 0.1169 -7.0356 < 0.001 ***
#> mu_C2 (mean) 1.0946 0.1141 9.5956 < 0.001 ***
#> mu_C3 (mean) 0.0492 0.1531 0.3212 0.7480
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# }