sjPlot | sjPlot - Data Visualization for Statistics in Social Science | Data Visualization library

I am trying to make an interaction plot in sjPlot showing percent probabiliites of my outcome under two conditions of my predictive variable. Everything works perfectly, except the show.values = T and sort.est = T arguments, which don't seem to do anything. Is there a way to get this to work? Or, if not, how can I extract the dataframe sjPlot is using to create this figure? Looking for some way to either label or tabulate the displayed probability values. Thank you!

Here is some example data and what I have so far:

I fitted a glm model and had to transform some variables with log1p. I now want to create a ggpredict plot with a backtransformed scale. I transformed the variables before using the glm function.

here's a sample of a few variables of my original data and my code:

I have imputed data saved as a mids object and am trying to adapt my usual workflow around imputed data. However, I cannot figure out how to use sjPlot's tab_corr() and tab_df() and psych's describe on a mids object.

My goal is to generate a table of descriptive statistics and a correlation matrix without averaging the imputed datasets together. I was able to generate correlations using miceadds::micombine.cor, but the output isn't formatted like a typical correlation matrix. I also can individually compute means, SDs, etc. of variables from the mids object, but I'm looking for something that will generate a table.

I have a summary regression model I want to put into a table. However, it keeps coming up with an error. Not sure what I am doing wrong here. I have included a reproducible data and steps I have taken below.

Is there a way to add the Statistic for each variable as a column in a tbl_regresion() with {gtsummary}? In Psychology is not uncommon for reviewers to expect this column in the tables.

When using {sjPlot}, just need to add the show.stat parameter, and the Statistic column will appear showing the t value from summary(model).

I have historically used sjPlot to create APA-style regression tables that export directly as a docx. Unfortunately, models based on imputed data (mipo objects) are not currently compatible with tab_model.

I am looking for a function similar to tab_model that can export APA-style regression tables directly to a Word Document in a single chunk without having to knit. Most packages I found (e.g., stargazer) seem to require knitting to create the table. Alternatively, if anyone knows a workaround to get mipo objects to work with tab_model, I would be most appreciative.

I would like to plot the estimates of the fixed effects of an lme4::lmer model. Currently, the sjPlot::plot_model output includes two additional plots that I do not want: SD (Observations) and SD (Intercept). How can I remove these two additional plots?

I have a dataset in a long format of 60 repeated measurements taken within 19 patients (ID). Patients have had a differing amount of measurements (2 measurements [n=11], followed by 5 measurements [n=5], 3 [n=1], 4 [n=1], and 6 measurements [n=1], with varying time-intervals (fu_time measured in years). The data looks as follows:

I have this list of tables that I've created by sjPlot

Where every elements contains a table like this

If I would like to create a report with RMarkdown or save them as a word file, would am I supposed to do?