Dear all in Statalist,

In our studies, we perform Precision test (closeness between repeated measurements) for the same blood sample analyzed in 3 analyzers of the same model placed at 3 different laboratories (Sites). The blood sample is analyzed in duplicates (Run) for 8 consecutive days (Day). The results are then analyzed in Analyse-it add-in for Excel to calculate the "Between" and "Within" SDs and CVs (%) for the Sites, Days, and Runs. The analysis in Analyse-it is called Measurement systems analysis (MSA).

As we try to perform all the statistical analyses in Stata now, I need help with performing the Precision test in Stata. By using the -xtset- and -xtsum- commands, I was able to get very similar results for the SDs of Between Day, Within Site, and Between Site; but not for Within Run and Between Run. I wonder if there is other ways for calculating the SDs and the CVs(%) for the different groups (within and between) that generate exactly the same results as those in Analyse-it based on the mean of T3 (3.871562)? And maybe the same table generated in Analyse-it (see the last code)?

My data look like this:
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input str8 id str19 date byte(site day run) float t3
"1170752+" "2017-10-04T08:59:35" 1 1 1 3.87
"1170752+" "2017-10-04T09:00:57" 1 1 1 3.93
"1170752+" "2017-10-04T13:38:17" 1 1 2 3.93
"1170752+" "2017-10-04T13:40:41" 1 1 2 3.91
"1170752+" "2017-10-06T07:14:34" 1 2 1 3.92
"1170752+" "2017-10-06T12:52:25" 1 2 1 3.91
"1170752+" "2017-10-06T15:10:00" 1 2 2 3.91
"1170752+" "2017-10-06T15:11:21" 1 2 2 3.98
"1170752+" "2017-10-09T07:33:06" 1 3 1 3.89
"1170752+" "2017-10-09T07:38:45" 1 3 1 3.91
"1170752+" "2017-10-09T12:41:51" 1 3 2 3.91
"1170752+" "2017-10-09T12:43:10" 1 3 2 3.92
"1170752+" "2017-10-10T07:34:53" 1 4 1 3.92
"1170752+" "2017-10-10T07:36:15" 1 4 1 3.92
"1170752+" "2017-10-10T15:23:59" 1 4 2 3.85
"1170752+" "2017-10-10T15:25:20" 1 4 2 3.95
"1170752+" "2017-10-11T07:25:29" 1 5 1 3.95
"1170752+" "2017-10-11T07:26:54" 1 5 1 3.94
"1170752+" "2017-10-11T15:04:10" 1 5 2  3.9
"1170752+" "2017-10-11T15:05:27" 1 5 2 3.92
"1170752+" "2017-10-12T07:34:30" 1 6 1 3.92
"1170752+" "2017-10-12T07:35:45" 1 6 1  3.9
"1170752+" "2017-10-12T13:34:37" 1 6 2 3.94
"1170752+" "2017-10-12T13:35:55" 1 6 2 3.91
"1170752+" "2017-10-13T07:18:52" 1 7 1 3.87
"1170752+" "2017-10-13T07:20:06" 1 7 1 3.93
"1170752+" "2017-10-13T14:17:51" 1 7 2 3.86
"1170752+" "2017-10-13T14:19:15" 1 7 2 3.89
"1170752+" "2017-10-16T08:42:13" 1 8 1 3.87
"1170752+" "2017-10-16T08:43:29" 1 8 1  3.9
"1170752+" "2017-10-16T14:39:51" 1 8 2  3.9
"1170752+" "2017-10-16T14:41:06" 1 8 2 3.87
"1170752+" "2017-09-26T13:33:15" 2 1 1 3.95
"1170752+" "2017-09-26T14:29:13" 2 1 1 3.83
"1170752+" "2017-09-26T16:06:37" 2 1 2 3.89
"1170752+" "2017-09-26T16:07:47" 2 1 2 3.88
"1170752+" "2017-09-27T08:55:48" 2 2 1 3.92
"1170752+" "2017-09-27T08:57:11" 2 2 1 3.86
"1170752+" "2017-09-27T17:00:45" 2 2 2 3.91
"1170752+" "2017-09-27T17:01:57" 2 2 2 3.88
"1170752+" "2017-09-28T10:26:13" 2 3 1 3.87
"1170752+" "2017-09-28T10:35:04" 2 3 1 3.88
"1170752+" "2017-09-28T20:22:30" 2 3 2  3.9
"1170752+" "2017-09-28T20:25:04" 2 3 2 3.82
"1170752+" "2017-09-29T08:30:44" 2 4 1 3.83
"1170752+" "2017-09-29T08:31:59" 2 4 1 3.82
"1170752+" "2017-09-29T16:39:24" 2 4 2  3.8
"1170752+" "2017-09-29T16:42:02" 2 4 2 3.87
"1170752+" "2017-10-02T08:36:05" 2 5 1 3.81
"1170752+" "2017-10-02T08:39:45" 2 5 1 3.81
"1170752+" "2017-10-02T17:05:34" 2 5 2 3.78
"1170752+" "2017-10-02T17:08:39" 2 5 2 3.84
"1170752+" "2017-10-04T08:15:45" 2 6 1 3.95
"1170752+" "2017-10-04T08:17:48" 2 6 1 3.88
"1170752+" "2017-10-04T16:11:11" 2 6 2 3.91
"1170752+" "2017-10-04T16:14:31" 2 6 2 3.91
"1170752+" "2017-10-06T09:25:57" 2 7 1 3.81
"1170752+" "2017-10-06T09:27:11" 2 7 1 3.84
"1170752+" "2017-10-06T19:58:50" 2 7 2 3.84
"1170752+" "2017-10-06T20:04:25" 2 7 2  3.8
"1170752+" "2017-10-07T13:59:14" 2 8 1  3.8
"1170752+" "2017-10-07T14:01:36" 2 8 1 3.83
"1170752+" "2017-10-07T15:49:51" 2 8 2 3.84
"1170752+" "2017-10-07T15:51:05" 2 8 2 3.78
"1170752+" "2017-10-11T07:29:34" 3 1 1 3.89
"1170752+" "2017-10-11T07:30:57" 3 1 1 3.85
"1170752+" "2017-10-11T15:08:08" 3 1 2 3.86
"1170752+" "2017-10-11T15:09:26" 3 1 2 3.96
"1170752+" "2017-10-12T07:38:28" 3 2 1 3.87
"1170752+" "2017-10-12T07:39:53" 3 2 1 3.86
"1170752+" "2017-10-12T13:38:39" 3 2 2 3.96
"1170752+" "2017-10-12T13:39:59" 3 2 2 3.92
"1170752+" "2017-10-13T07:22:53" 3 3 1 3.85
"1170752+" "2017-10-13T07:24:07" 3 3 1 3.85
"1170752+" "2017-10-13T14:21:21" 3 3 2 3.84
"1170752+" "2017-10-13T14:22:35" 3 3 2 3.81
"1170752+" "2017-10-16T08:46:11" 3 4 1 3.81
"1170752+" "2017-10-16T08:47:31" 3 4 1 3.81
"1170752+" "2017-10-16T14:43:48" 3 4 2 3.83
"1170752+" "2017-10-16T14:45:05" 3 4 2 3.79
"1170752+" "2017-10-17T07:24:32" 3 5 1  3.8
"1170752+" "2017-10-17T07:26:29" 3 5 1 3.81
"1170752+" "2017-10-17T15:15:41" 3 5 2  3.8
"1170752+" "2017-10-17T15:16:56" 3 5 2 3.91
"1170752+" "2017-10-18T06:50:14" 3 6 1 3.79
"1170752+" "2017-10-18T07:37:53" 3 6 1 3.91
"1170752+" "2017-10-18T07:39:13" 3 6 2 3.86
"1170752+" "2017-10-18T13:40:53" 3 6 2 3.86
"1170752+" "2017-10-19T07:59:16" 3 7 1 3.87
"1170752+" "2017-10-19T08:00:46" 3 7 1 3.85
"1170752+" "2017-10-19T13:42:18" 3 7 2  3.8
"1170752+" "2017-10-19T13:44:14" 3 7 2 3.82
"1170752+" "2017-10-20T07:18:04" 3 8 1 3.82
"1170752+" "2017-10-20T07:19:33" 3 8 1 3.85
"1170752+" "2017-10-20T14:51:12" 3 8 2 3.85
"1170752+" "2017-10-20T14:52:32" 3 8 2 3.87
end
Here are the codes I used to calculate the SDs. Yet, the results are not exactly the same as those generated in Analyse-it.
Code:
/* similar results */
xtset day
xtsum t3

/* similar results */
xtset site
xtsum t3
     
/* different results */
xtset run
xtsum t3
Here are the results generated by Analyse-it.
Code:
Component CV Exact/Satterthwaite 95% CI SD Expected SD/CV p-value
Within Run 0,9% 0,8% to 1,1% 0,035 2,5%
1,00001
Between Run 0,0% 0,000
Between Day 0,7% 0,028
Within Site 1,2% 1,0% to 1,4% 0,045
Between Site 0,8% 0,031
Total 1,4% 1,0% to 2,3% 0,054 2,5%
0,98661 
 H0: σ ≤ σ0
The imprecision is less than or equal to the expected imprecision.
H1: σ > σ0
The imprecision is greater than the expected imprecision.
1 Do not reject the null hypothesis at the 5% significance level.
I appreciate you help.