# Getting different standard errors using mplus and lmer in R

I am fitting the same mixed effects model using mplus and lmer in R. Since mplus uses full information maximum likelihood (FIML) method, I selected REML=FALSE in the lmer package.

I am getting same point estimates from two models. However the standard errors are different.

The results using lmer pacakge

glm_mo=lmer(DEP ~ gender + (1| cluster), data=data_cmd_long, REML = FALSE)


The results using mplus

    MODEL RESULTS

Two-Tailed
Estimate       S.E.  Est./S.E.    P-Value

Within Level

DEP        ON
GENDER             0.088      0.015      5.973      0.000

Residual Variances
DEP                0.072      0.004     17.988      0.000

Between Level

Means
DEP                0.689      0.020     34.606      0.000

Variances
DEP                0.001      0.001      1.531      0.126


What may be the reason that causing different standard errors?

I thought by defining REML=FALSE make results equivalent using two approaches.

Any help will be highly appreciated.

Thank you.

Edit:

This my input code for mplus

Variable:
names =  aid dep gender cluster ;
usevariables = dep gender cluster ;
within= gender;
MISSING IS cluster (9999) dep (9999);

CLUSTER = cluster;

Analysis: TYPE = TWOLEVEL random ;
estimator = mlr;

Model:
%WITHIN%
dep on gender  ;
%BETWEEN%
dep;


Some other related portion of the output from mplus

Estimator                                                       ML
Information matrix                                        OBSERVED
Maximum number of iterations                                   100
Convergence criterion                                    0.100D-05
Maximum number of EM iterations                                500
Convergence criteria for the EM algorithm
Loglikelihood change                                   0.100D-02
Relative loglikelihood change                          0.100D-05
Derivative                                             0.100D-03
Minimum variance                                         0.100D-03
Maximum number of steepest descent iterations                   20
Maximum number of iterations for H1                           2000
Convergence criterion for H1                             0.100D-03
Optimization algorithm                                         EMA


Results based on ML option in mplus

MODEL RESULTS

Two-Tailed
Estimate       S.E.  Est./S.E.    P-Value

Within Level

DEP        ON
GENDER             0.088      0.014      6.083      0.000

Residual Variances
DEP                0.072      0.003     25.654      0.000

Between Level

Means
DEP                0.689      0.022     30.934      0.000

Variances
DEP                0.001      0.001      1.515      0.130

• What estimator did you use in Mplus? Can you post more of your input and output from Mplus? Feb 26, 2021 at 17:41
• @JeremyMiles Thank you for the comment. I updated the question with more information. Feb 26, 2021 at 17:46
• Your estimator is MLR, not ML. Feb 26, 2021 at 17:49
• And you have missing data, which lmer and Mplus handle differently. (I think). Feb 26, 2021 at 17:50
• @JeremyMiles Yeah both programs have used 1422 rows and 129 clusters. I updated the question with the result based on ML option and now it s more comparable than previously. Thank you for the suggestion. Feb 26, 2021 at 17:59