r - lsmeans and difflsmeans return no output for lmer object -

i'm trying calculate confidence intervals fixed effects in lmer mixed model, , difflsmeans , lsmeans return empty table. i've tried lme() having trouble model convergence (hence using lmer).

the data (where bout dependent level 1 variable , twaverage independent level 2 variable of interest , sex, location , ra further nesting levels):

id  bout twaverage  sex location    ra 1   17  3.748333333 1   big society 1337 1   59  3.748333333 1   big society 1337 1   14  3.748333333 1   big society 1337 1   9   3.748333333 1   big society 1337 1   9   3.748333333 1   big society 1337 1   14  3.748333333 1   big society 1337 1   21  3.748333333 1   big society 1337 2   40  3.055833333 0   big society 1337 2   63  3.055833333 0   big society 1337 2   7   3.055833333 0   big society 1337 2   75  3.055833333 0   big society 1337 2   13  3.055833333 0   big society 1337 2   3   3.055833333 0   big society 1337 2   16  3.055833333 0   big society 1337 3   103 3.696666667 1   big society 1337 3   14  3.696666667 1   big society 1337 3   2   3.696666667 1   big society 1337 3   32  3.696666667 1   big society 1337 

my model specification looks this:

groupsizerandom = lmer(bout ~ twaverage + (twaverage|id), data, reml = f) 

i'm calling lsmeans (which understand should give me confidence intervals fixed effects in model):

lsmeans(groupsizerandom,test.effs = null) 

however, returns empty table (with no values):

least squares means table:      estimate standard error df t-value lower ci upper ci p-value 

anyone know why? or how calculate cis model i've specified above?

there few issues here.

• if want confidence intervals of fixed-effect parameters, can likelihood profile cis via confint(groupsizerandom) or wald cis via confint(groupsizerandom,method="wald") (see ?confint.mermod).
• as pointed out in comments, there 2 lsmeans functions
  • lmertest::lsmeans report lsmeans factor variables. pointed out in comments, "factor" has specific meaning in r - means categorical predictor (independent) variable. twaverage continuous predictor, in r terms it's not "factor".
  • lsmeans::lsmeans give ask if use lsmeans(groupsizerandom,spec="twaverage") ...