This class contains the results of 2-Stage Maximum Likelihood (TSML) estimation for missing data. The summary, anova, vcov methods return corrected SEs and test statistics. Other methods are simply wrappers around the corresponding '>lavaan methods.
Objects can be created via the twostage function.
saturated:A fitted '>lavaan object containing the saturated model results.
target:A fitted '>lavaan object containing the target/hypothesized model results.
baseline:A fitted '>lavaan object containing the baseline/null model results.
auxNames:A character string (potentially of length == 0) of any auxiliary variable names, if used.
signature(object = "twostage", h1 = NULL, baseline = FALSE: The anova function returns the residual-based chi-squared test statistic result, as well as the scaled chi-squared test statistic result, for the model in the target slot, or for the model in the baseline slot if baseline = TRUE. The user can also provide a single additional twostage object to the h1 argument, in which case anova returns residual-based and scaled chi-squared difference test results, under the assumption that the models are nested. The models will be automatically sorted according their degrees of freedom.
signature(object = "twostage"): The show function is used to display the results of the anova method, as well as the header of the (uncorrected) target model results.
signature(object = "twostage", ...): The summary function prints the same information from the show method, but also provides (and returns) the output of parameterEstimates(object@target, ...) with corrected SEs, test statistics, and confidence intervals. Additional arguments can be passed to parameterEstimates, including fmi = TRUE to provide an estimate of the fraction of missing information.
signature(object = "twostage", baseline = FALSE: Returns the asymptotic covariance matrix of the estimated parameters (corrected for additional uncertainty due to missing data) for the model in the target slot, or for the model in the baseline slot if baseline = TRUE.
signature(object = "twostage", type = c("ntotal", "ngroups", "n.per.group", "norig", "patterns", "coverage")): The nobs function will return the total sample sized used in the analysis by default. Also available are the number of groups or the sample size per group, the original sample size (if any rows were deleted because all variables were missing), the missing data patterns, and the matrix of coverage (diagonal is the proportion of sample observed on each variable, and off-diagonal is the proportion observed for both of each pair of variables).
signature(object = "twostage", type = c("free", "user"): This is simply a wrapper around the corresponding '>lavaan method, providing point estimates from the target slot.
signature(object = "twostage", model = c("target", "saturated", "baseline"): This is simply a wrapper around the corresponding '>lavaan method, providing model-implied sample moments from the slot specified in the model argument.
signature(object = "twostage", model = c("target", "saturated", "baseline"): an alias for fitted.values.
signature(object = "twostage", type = c("raw", "cor", "normalized", "standardized"): This is simply a wrapper around the corresponding '>lavaan method, providing residuals of the specified type from the target slot.
signature(object = "twostage", model = c("raw", "cor", "normalized", "standardized"): an alias for residuals.
# NOT RUN {
# See the example from the twostage function
# }
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