MLPE vs ML in lmer (landscape genetics)

Question

[RedSkyPlum]

I am trying to conduct some landscape genetics analysis by testing association between landscape resistance matrices and pairwise genetic distances using linear mixed models.

When I run lmer package, I am unable to incorporate MLPE (Maximum likelihood population effects - regularly referenced and used when conducting this analysis). I am unable to find how to run MLPE approach in lmer anywhere too.

Am I misunderstanding this, are they (MLPE and ML) the same thing as I appear to be able to run ML.

EDIT: Includes code:

model_5 <- lmer(Genetic.Distance ~ (1 | Topography),
                            data = file, REML = FALSE)
summary(model_5)

OUTPUT

Linear mixed model fit by maximum likelihood  ['lmerMod']
Formula: Genetic.Distance ~ (1 | Topography)
   Data: file

 AIC      BIC   logLik deviance df.resid 
-68399.5 -68377.3  34202.8 -68405.5    12087 

Any advice, guidance or resources on how to conduct MLPE in lme4 would be much appreciated!

Thanks in advance!

Answer 1

[stacy_biology97]

They are the same thing.