TABLE 3.

Summary of imputation methods for mixed-type longitudinal data

Approach	Data format	Method	Imputation models
FCS			Imputation model for binary variables	Imputation model for count variables
	Wide	FCS-Standard (LM)	Logistic regression	Linear regression
		FCS-Standard (PMM)	Logistic regression	Predictive mean matching
		FCS-Standard (Poisson)	Logistic regression	Poisson regression
	Long	FCS-LMM-latent	Multilevel linear regression on latent variables	Multilevel linear regression
		FCS-GLMM (Gaussian)	Multilevel logistic regression	Multilevel linear regression
		FCS-GLMM (Poisson)	Multilevel logistic regression	Multilevel Poisson regression
JM	Wide	JM-GL	General location model
	Long	JM-MLMM-latent (common)	Multivariate multilevel linear model with latent variables and homoscedastic within-subject variance
		JM-MLMM-latent (random)	Multivariate multilevel linear model with latent variables and heteroscedastic within-subject variance
		JM-MGLMM	Multivariate multilevel generalized linear model using a logit and log link for binary, count variables