LMest: problem introducing covariates to the measurement model when fitting a Latent Markov Model to continuous data

Question

I am working with longitudinal continuous data that reflect the linguistic abilities of children. In that regard I seek to make a Latent Transition Model, more exact a Latent Markov Model using the LMest package in R. As far as I have understood this means creating both a measurement model and subsequently a latent model, both in which covariates (X) can be reduced, however I fail when I try to add them to the measurement model. Can anyone tell me why?

##### SIMULATED DATA OF THE SAME NATURE 
ID <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,3)
time <-  c(0,1,2,3,4,5,6,7,8,0,1,2,3,4,5,6,7,8,0,1,2,3,4,5,6,7,8)
gender <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1)
response_y <- c(NA, 0.15, 0.2, 0.4, 0.64, NA, 0.85, 0.89, NA, 0.02, NA, 0.01, 0.11, 0.35, 0.63, NA, NA, NA, NA, 0.3, NA, 0.56, 0.84, 0.81, 0.9, NA, NA)
response_y1 <- c(NA, 0.1, 0.3, 0.5, NA, NA, 0.7, 0.89, NA, NA, NA, 0.01, 0.11, 0.35, NA, NA, NA, NA, NA, 0.3, NA, 0.56, 0.84, NA, 0.9, 0.91, NA)

d = data.frame(ID, time, gender, response_y)

I have so far tried to model it like this:

library(LMest)

## COVARIATES INTRODUCED TO THE MEASUREMENT MODEL (gives error)
lmestCont(responsesFormula = response_y + response_y1 ~ gender, latentFormula = NULL, index = c("ID", "time"), k = 1:5, data = dt$data, modBasic = 1, output = TRUE, tol = 10^-5, out_se = TRUE)

But keep getting this error:

Warning: multivariate data are not allowed; only the first response variable is considered Steps of EM: 1...2...3...4...5...6...7...8...9...10...11...12...13...14...15...16...17...18...19...20...21...22...23...24...25...26...27...28...29...30...31...32...33...34...35...36...37...38...39...40...41...42...43...44... Missing data in the dataset. imp.mix function (mix package) used for imputation. Error in aicv[kv] <- out[[kv]]$aic : replacement has length zero

When introducing the covariates to the latent model it works, and looks like this:

## COVARIATES INTRODUCED TO THE LATENT MODEL (RUNS)
mod_con <- lmestCont(responsesFormula = response_y+ response_y1 ~ NULL, latentFormula = ~ gender | gender, index = c("ID", "time"), k = 1:5, data = dt$data, modBasic = 1, output = TRUE, tol = 10^-5, out_se = TRUE)

All kinds of advise are happily received - also on the LMest in general, maybe I have misunderstood something!!! thanks