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Jul 3, 2019, 4:08:37 PM7/3/19

to lavaan

I am trying to run a moderation model, where X=INNSUPP; M=lnTam; and Y = lnTam.

Initially, the script run without problem. However, when I opened R again and I tried to run the same code, I get the following message:

`lavaan WARNING: some observed variances are (at least) a factor 1000 times larger than others; use varTable(fit) to investigatelavaan WARNING: syntax contains parameters involving exogenous covariates; switching to fixed.x = FALSE`

The code is

# CENTRANDO LOS DATOS SME <- SME %>% mutate_at(vars(lnTam, INNSUPP, MAMB), funs(c=scale)) # create interaction term between centered X (socst) and W (math) SME <- SME %>% mutate(INNSUPP_x_lnTam = INNSUPP_c * lnTam_c) # parameters moderation_model <- ' # regressions MAMB ~ b1*INNSUPP_c MAMB ~ b2*lnTam_c MAMB ~ b3*INNSUPP_x_lnTam # define mean parameter label for centered math for use in simple slopes lnTam_c ~ lnTam.mean*1 # define variance parameter label for centered math for use in simple slopes lnTam_c ~~ lnTam.var*lnTam_c # simple slopes for condition effect SD.below := b1 + b3*(lnTam.mean - sqrt(lnTam.var)) mean := b1 + b3*(lnTam.mean) SD.above := b1 + b3*(lnTam.mean + sqrt(lnTam.var)) ' # fit the model using nonparametric bootstrapping (this takes some time) sem1 <- sem(model = moderation_model, data = SME, se = "bootstrap", bootstrap = 1000) # fit measures summary(sem1, fit.measures = TRUE, standardized = TRUE, rsquare = TRUE) #compute bias-corrected estimates of bootstrapped confidence intervals parameterEstimates(sem1, boot.ci.type = "bca.simple", level = .95, ci = TRUE, standardized = FALSE) ```

`Thank you very much in advance!!!`

Jul 31, 2019, 7:49:56 PM7/31/19

to lavaan

Do vartable(fit) to find the offending variables, then multiple of divide by a factor of 10.

Best,

Nick

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