An object of class lavaan.mi

See parameterEstimates. output can also be passed to fitMeasures.

logical indicating whether to include the Fraction Missing Information (FMI) for parameter estimates in the summary output (see Value section).

logical. If TRUE (default), the vcov method will calculate the pooled covariance matrix by scaling the within-imputation component by the ARIV (see Enders, 2010, p. 235, for definition and formula). Otherwise, the pooled matrix is calculated as the weighted sum of the within-imputation and between-imputation components (see Enders, 2010, ch. 8, for details). This in turn affects how the summary method calcualtes its pooled standard errors, as well as the Wald test (lavTestWald.mi).

character vector specifying criteria for omitting imputations from pooled results. Can include any of c("no.conv", "no.se", "no.npd"), the first 2 of which are the default setting, which excludes any imputations that did not converge or for which standard errors could not be computed. The last option ("no.npd") would exclude any imputations which yielded a nonpositive definite covariance matrix for observed or latent variables, which would include any "improper solutions" such as Heywood cases. NPD solutions are not excluded by default because they are likely to occur due to sampling error, especially in small samples. However, gross model misspecification could also cause NPD solutions, users can compare pooled results with and without this setting as a sensitivity analysis to see whether some imputations warrant further investigation. Specific imputation numbers can also be included in this argument, in case users want to apply their own custom omission criteria (or simulations can use different numbers of imputations without redundantly refitting the model).

logical. If FALSE (typically a default, but see Value section for details using various methods), pooled tests (of fit or pooled estimates) will be F or t statistics with associated degrees of freedom (df). If TRUE, the (denominator) df are assumed to be sufficiently large for a t statistic to follow a normal distribution, so it is printed as a z statisic; likewise, F times its numerator df is printed, assumed to follow a χ^2 distribution.

See fitMeasures. summary(object, fit.measures = TRUE) will print (but not return) a table of fit measures to the console.

Additional arguments passed to lavTestLRT.mi, or subsequently to lavTestLRT.

logical (default: TRUE) indicating whether the nobs method should return the total sample size or (if FALSE) a vector of group sample sizes.

The meaning of this argument varies depending on which method it it used for. Find detailed descriptions in the Value section under coef, vcov, and residuals.

logical indicating whether the coef output should include parameter labels. Default is TRUE.

signature(object = "lavaan.mi", type = "free", labels = TRUE, omit.imps = c("no.conv","no.se")): See lavaan. Returns the pooled point estimates (i.e., averaged across imputed data sets; see Rubin, 1987).

signature(object = "lavaan.mi", scale.W = TRUE, omit.imps = c("no.conv","no.se"), type = c("pooled","between","within","ariv")): By default, returns the pooled covariance matrix of parameter estimates (type = "pooled"), the within-imputations covariance matrix (type = "within"), the between-imputations covariance matrix (type = "between"), or the average relative increase in variance (type = "ariv") due to missing data.

signature(object = "lavaan.mi", omit.imps = c("no.conv","no.se")): See lavaan. Returns model-implied moments, evaluated at the pooled point estimates.

alias for fitted.values

signature(object = "lavaan.mi", type = c("raw","cor"), omit.imps = c("no.conv","no.se")): See lavaan. By default (type = "raw"), returns the difference between the model-implied moments from fitted.values and the pooled observed moments (i.e., averaged across imputed data sets). Standardized residuals are also available, using Bollen's (type = "cor" or "cor.bollen") or Bentler's (type = "cor.bentler") formulas.

alias for residuals

signature(object = "lavaan.mi", total = TRUE): either the total (default) sample size or a vector of group sample sizes (total = FALSE).

signature(object = "lavaan.mi", ...): Returns a test of model fit for a single model (object) or test(s) of the difference(s) in fit between nested models passed via .... See lavTestLRT.mi and compareFit for details.

signature(object = "lavaan.mi", fit.measures = "all", baseline.model = NULL, output = "vector", omit.imps = c("no.conv","no.se"), ...): See lavaan's fitMeasures for details. Pass additional arguments to lavTestLRT.mi via ....

alias for fitMeasures.

signature(object = "lavaan.mi"): returns a message about convergence rates and estimation problems (if applicable) across imputed data sets.

signature(object = "lavaan.mi", se = TRUE, ci = FALSE, level = .95, standardized = FALSE, rsquare = FALSE, fmi = FALSE, scale.W = !asymptotic, omit.imps = c("no.conv","no.se"), asymptotic = FALSE, header = TRUE, output = "text", fit.measures = FALSE, ...): see parameterEstimates for details. By default, summary returns pooled point and SE estimates, along with t test statistics and their associated df and p values. If ci = TRUE, confidence intervales are returned with the specified confidence level (default 95% CI). If asymptotic = TRUE, z instead of t tests are returned. standardized solution(s) can also be requested by name ("std.lv" or "std.all") or both are returned with TRUE. R-squared for endogenous variables can be requested, as well as the Fraction Missing Information (FMI) for parameter estimates. By default, the output will appear like lavaan's summary output, but if output == "data.frame", the returned data.frame will resemble the parameterEstimates output. The scale.W argument is passed to vcov (see description above). Setting fit.measures=TRUE will additionally print fit measures to the console, but they will not be returned; additional arguments may be passed via ... to fitMeasures and subsequently to lavTestLRT.mi.