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singmann
emmeans for mixed models is very slow
Not sure why this is happening... See example below (6 min vc 500ms)
library(afex)
library(emmeans)
data(obk.long, package = "afex")
fit_lmm <- mixed(value ~ treatment * gender * phase * hour + (phase * hour || id),
data = obk.long,
method = "S", # p-value method
expand_re = TRUE)
#> Contrasts set to contr.sum for the following variables: treatment, gender, phase, hour, id
#> Fitting one lmer() model.
#> boundary (singular) fit: see ?isSingular
#> [DONE]
#> Calculating p-values. [DONE]
emm_options(lmer.df = "satterthwaite")
t1 <- Sys.time()
joint_tests(fit_lmm, by = "gender")
#> gender = F:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 1.329 0.3077
#> phase 2 14.04 4.875 0.0247
#> hour 4 13.47 8.830 0.0010
#> treatment:phase 4 14.04 2.333 0.1063
#> treatment:hour 8 13.47 0.395 0.9046
#> phase:hour 8 11.19 1.264 0.3495
#> treatment:phase:hour 16 11.19 0.516 0.8892
#>
#> gender = M:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 6.158 0.0181
#> phase 2 14.04 9.048 0.0030
#> hour 4 13.47 4.835 0.0124
#> treatment:phase 4 14.04 2.959 0.0576
#> treatment:hour 8 13.47 0.378 0.9143
#> phase:hour 8 11.19 0.778 0.6309
#> treatment:phase:hour 16 11.19 0.371 0.9651
Sys.time() - t1
#> Time difference of 6.453859 mins
t2 <- Sys.time()
joint_tests(fit_lmm$full_model, by = "gender")
#> gender = F:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 1.329 0.3077
#> phase 2 14.04 4.875 0.0247
#> hour 4 13.47 8.830 0.0010
#> treatment:phase 4 14.04 2.333 0.1063
#> treatment:hour 8 13.47 0.395 0.9046
#> phase:hour 8 11.19 1.264 0.3495
#> treatment:phase:hour 16 11.19 0.516 0.8892
#>
#> gender = M:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 6.158 0.0181
#> phase 2 14.04 9.048 0.0030
#> hour 4 13.47 4.835 0.0124
#> treatment:phase 4 14.04 2.959 0.0576
#> treatment:hour 8 13.47 0.378 0.9143
#> phase:hour 8 11.19 0.778 0.6309
#> treatment:phase:hour 16 11.19 0.371 0.9651
Sys.time() - t2
#> Time difference of 0.5516829 secs
That is very surprising. Thanks for the report. Also, sorry for the delay at the moment.
It took me only around 4 years, but I hope this is fixed now. I just needed to deactivate a check in the emmeans() method that I believe was needed back in the days when first implementing it but seems unnecessary now.
If you have the time to check if it works and makes stuff much faster, please let me know. I will close this issue now, feel free to reopen if necessary.
suppressPackageStartupMessages(library(afex))
library(emmeans)
data(obk.long, package = "afex")
fit_lmm <- mixed(value ~ treatment * gender * phase * hour + (phase + hour || id),
data = obk.long,
method = "S", # p-value method
expand_re = TRUE)
#> Contrasts set to contr.sum for the following variables: treatment, gender, phase, hour, id
#> boundary (singular) fit: see help('isSingular')
emm_options(lmer.df = "satterthwaite")
t1 <- Sys.time()
joint_tests(fit_lmm, by = "gender")
#> gender = F:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 1.329 0.3077
#> phase 2 12.49 7.693 0.0066
#> hour 4 16.25 7.522 0.0013
#> treatment:phase 4 12.49 4.382 0.0194
#> treatment:hour 8 16.25 0.331 0.9415
#> phase:hour 8 105.73 1.044 0.4080
#> treatment:phase:hour 16 105.73 0.517 0.9335
#>
#> gender = M:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 6.158 0.0181
#> phase 2 12.49 13.696 0.0007
#> hour 4 16.25 4.149 0.0168
#> treatment:phase 4 12.49 1.763 0.1986
#> treatment:hour 8 16.25 0.318 0.9478
#> phase:hour 8 105.73 1.209 0.3009
#> treatment:phase:hour 16 105.73 0.613 0.8669
Sys.time() - t1
#> Time difference of 0.5449231 secs
t2 <- Sys.time()
joint_tests(fit_lmm$full_model, by = "gender")
#> gender = F:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 1.329 0.3077
#> phase 2 12.49 7.693 0.0066
#> hour 4 16.25 7.522 0.0013
#> treatment:phase 4 12.49 4.382 0.0194
#> treatment:hour 8 16.25 0.331 0.9415
#> phase:hour 8 105.73 1.044 0.4080
#> treatment:phase:hour 16 105.73 0.517 0.9335
#>
#> gender = M:
#> model term df1 df2 F.ratio p.value
#> treatment 2 10.00 6.158 0.0181
#> phase 2 12.49 13.696 0.0007
#> hour 4 16.25 4.149 0.0168
#> treatment:phase 4 12.49 1.763 0.1986
#> treatment:hour 8 16.25 0.318 0.9478
#> phase:hour 8 105.73 1.209 0.3009
#> treatment:phase:hour 16 105.73 0.613 0.8669
Sys.time() - t2
#> Time difference of 0.4634171 secs
Created on 2024-04-07 with reprex v2.1.0