r - Predicted(?) values from an lmer model -

i have data frame of bird counts. have participants id number, number of birds counted, year counted them, lat , long coordinates, , effort. have made model:

model = lmer(count~year+lat+long+effort+(1|participant), data = df) 

i want model plot predicted values same data set. so, data 1997-2017, , want model give me predicted values each year. want plot these, final plot have predicted count on y-axis, , year (categorical) on x-axis. each year have 1 data point w/ confidence interval.

i have tried figuring out predict(), i'm not quite sure how use want. seems need new data frame, don't have new data set run through model predict future count. want model go , work on previous data put already, based off of beta values in output of summary(model).

i found thread, , seems i'm looking do, can't sjplot dependencies download, sjlabelled throws error every time: how plot predicted values standard errors lmer model results?

you try ggeffects-package, used in forthcoming sjplot-update plot predicted values.

library(ggeffects) dat <- ggpredict(model, terms = "dat") plot(dat) 

if you're missing dependencies, try:

install.packages(   c("sjlabelled", "sjmisc", "sjstats", "ggeffects", "sjplot"),   dependencies = true ) 

you may want install ggeffects github, since current dev-version has fixes , improvements mixed models.

devtools::install_github("strengejacke/ggeffects")