creating a table with mean plus/minus SD in each cell

Hello! I'm using Stata 14.1 on Windows. I am creating a table that has mean plus/minus standard deviation for several different variables. The variables are mean scores for Likert scale surveys. Each question is scored from 0-100 (0, 25,50, 75, or 100), and a participant's survey score is the mean of their responses to each question. The table will have a mean and SD of each participant's survey score. I can generate those values fine with -summary- or -collapse-, but getting those values into a table (with mean and SD in the same cell) eludes me—so far I’ve been copying from Stata into Word by hand. I've tried a few ways (like using -matrix-, or using r() to call stored results) but haven't gotten any to work.

My data is confidential so I generated fake data in Stata using rnormal (mean 73, SD 15). Here's a sample of the generated data, let me know if there's a better way to upload it:
Array


I tried using the estout package:

Code:

estpost summarize pql_c_total_mean_wk0 pql_c_pf_mean_wk0 pql_c_ef_mean_wk0 pql_c_sf_mean_wk0 pql_c_sch_mean_wk0 qol_c_total_mean_wk0 qol_c_self_mean_wk0 qol_c_soc_mean_wk0 qol_c_env_mean_wk0 ///
    pql_c_total_mean_wk21 pql_c_pf_mean_wk21 pql_c_ef_mean_wk21 pql_c_sf_mean_wk21 pql_c_sch_mean_wk21 qol_c_total_mean_wk21 qol_c_self_mean_wk21 qol_c_soc_mean_wk21 qol_c_env_mean_wk21 ///
    pql_c_total_mean_6m pql_c_pf_mean_6m pql_c_ef_mean_6m pql_c_sf_mean_6m pql_c_sch_mean_6m qol_c_total_mean_6m qol_c_self_mean_6m qol_c_soc_mean_6m qol_c_env_mean_6m // gen table with mean and sd
eststo summstats
esttab summstats using "X:\Mark\Writing\Output\table3.csv", replace main(mean %6.1f) aux(sd %6.1f) noparentheses

but the resulting excel file has a bunch of blank space and would require a lot of copy/pasting and doesn't have the plus/minus symbol. Additionally, numbers are actually formulas: ="17.3" instead of 17.3.
Array


I also tried using collapse: my plan was to use the concatenate function in excel to concatenate the mean, plus/minus symbol, and the SD, then paste into word.

Code:

preserve
collapse (mean) pql_c_total_mean_wk0 pql_c_pf_mean_wk0 pql_c_ef_mean_wk0 pql_c_sf_mean_wk0 pql_c_sch_mean_wk0 qol_c_total_mean_wk0 qol_c_self_mean_wk0 qol_c_soc_mean_wk0 qol_c_env_mean_wk0 ///
    pql_c_total_mean_wk21 pql_c_pf_mean_wk21 pql_c_ef_mean_wk21 pql_c_sf_mean_wk21 pql_c_sch_mean_wk21 qol_c_total_mean_wk21 qol_c_self_mean_wk21 qol_c_soc_mean_wk21 qol_c_env_mean_wk21 ///
    pql_c_total_mean_6m pql_c_pf_mean_6m pql_c_ef_mean_6m pql_c_sf_mean_6m pql_c_sch_mean_6m qol_c_total_mean_6m qol_c_self_mean_6m qol_c_soc_mean_6m qol_c_env_mean_6m
ds
foreach var in `r(varlist)' {
    replace `var' = round(`var', 0.1)
}
export excel using "\\childrens\research\nik\Mark\Writing\Output\table3.xlsx", sheet(mean) sheetreplace
restore

preserve
collapse (sd) pql_c_total_mean_wk0 pql_c_pf_mean_wk0 pql_c_ef_mean_wk0 pql_c_sf_mean_wk0 pql_c_sch_mean_wk0 qol_c_total_mean_wk0 qol_c_self_mean_wk0 qol_c_soc_mean_wk0 qol_c_env_mean_wk0 ///
    pql_c_total_mean_wk21 pql_c_pf_mean_wk21 pql_c_ef_mean_wk21 pql_c_sf_mean_wk21 pql_c_sch_mean_wk21 qol_c_total_mean_wk21 qol_c_self_mean_wk21 qol_c_soc_mean_wk21 qol_c_env_mean_wk21 ///
    pql_c_total_mean_6m pql_c_pf_mean_6m pql_c_ef_mean_6m pql_c_sf_mean_6m pql_c_sch_mean_6m qol_c_total_mean_6m qol_c_self_mean_6m qol_c_soc_mean_6m qol_c_env_mean_6m
ds
foreach var in `r(varlist)' {
    replace `var' = round(`var', 0.1)
}
export excel using "\\childrens\research\nik\Mark\Writing\Output\table3.xlsx", sheet(sd) sheetreplace
restore

The exported excel file had too many decimals, so I tried using -round- but the excel file still went to 13 decimals. I used -round- then -tostring-, which worked in Stata but the excel file had what I think is a floating point error (e.g. number is 72.80000305 instead of 72.8). Next I tried to change the collapsed variables from float to int using -recast-:

Code:

ds
foreach var in `r(varlist)' {
    recast int `var'
}

but the output said "1 value would be changed; not changed".

Here's an example of the table I'm going for, with fake means/SDs:
Array


I first used collapse to generate the means and SDs all at once (instead of separately like in my 2nd block of code), but that resulted in a single "observation" where half the variables were means and half were SDs, and I couldn't see an easy way to export them (I'll be making more tables, so doing 15 or so concatenate functions would be slower than copying by hand). Is there a way to have collapse create two "observations," where one row is means and the second is SDs? Because if so, reshaping it and then using concatenate would work really well.