[R-meta] Coding for length of time in longitudinal studies given its use in meta-regression

Farzad Keyhan |@keyh@n|h@ @end|ng |rom gm@||@com
Tue May 18 21:29:29 CEST 2021


Oops! the data in the link is correct but the copy-pasted data was not
showing correctly. Here I'm attaching the correct copy-pasted data again:

  study    mT   sdT nT    mC   sdC nC group length time
1     x 67.59 19.26 17 51.90 28.32 20     1      0    0
2     x 53.11 21.73 18 51.90 28.32 20     2      0    0
3     x 59.35 18.39 20 51.90 28.32 20     3      0    0
4     x 82.53 14.33 17 52.75 23.26 20     1      0    1
5     x 77.50 16.07 18 52.75 23.26 20     2      0    1
6     x 81.25 13.00 20 52.75 23.26 20     3      0    1
7     x 82.65 15.47 17 63.90 18.89 20     1      7    2
8     x 76.78 20.67 18 63.90 18.89 20     2      7    2
9     x 80.05 12.09 20 63.90 18.89 20     3      7    2

On Tue, May 18, 2021 at 2:23 PM Farzad Keyhan <f.keyhaniha using gmail.com> wrote:

> Dear Michael and list members,
>
> Thank you for your response. May I clarify the following:
>
> 1) We have a "continuous" moderator called `length` showing the "amount of
> time" allowed between the last treatment and each post-test in each of our
> longitudinal studies.
>
> 2) QUESTION: Since `length` is a moderator that only applies to
> "post-tests" (see definition above) and NOT to the "pre-tests", would it be
> accurate (i.e., from the perspective of using `length` in meta-regression)
> to put "0" for all  "pre-test" rows in each study when coding for `length`?
>
> 3) An example coded study (per your request, I'm also sharing a link for
> easier access to this one example coded study). In this one example coded
> study, descriptives are denoted by: mT,sdT,nTmC,sdC,nC. Also, 'group'
> denotes the treatment group index, and 'time' is a time point indicator.
>
>  example_of_a_coded_study <- read.csv("
> https://raw.githubusercontent.com/hkil/m/master/1.csv")
>
>      study         mT      sdT  nT     mC      sdC nC  group  length time
> 13   xxx    67.590 19.260 17 51.900 28.320 20         1       0    0
> 14   xxx    67.590 19.260 17 51.900 28.320 20         1       0    0
> 15   xxx    53.110 21.730 18 51.900 28.320 20         2       0    0
> 16   xxx    53.110 21.730 18 51.900 28.320 20         2       0    0
> 17   xxx    59.350 18.390 20 51.900 28.320 20         3       0    0
> 18   xxx    59.350 18.390 20 51.900 28.320 20         3       0    0
> 19   xxx    82.530 14.330 17 52.750 23.260 20         1       0    1
> 20   xxx    77.500 16.070 18 52.750 23.260 20         2       0    1
> 21   xxx    81.250 13.000 20 52.750 23.260 20         3       0    1
> 22   xxx    82.650 15.470 17 63.900 18.890 20         1       7    2
> 23   xxx    76.780 20.670 18 63.900 18.890 20         2       7    2
> 24   xxx    80.050 12.090 20 63.900 18.890 20         3       7    2
>
> On Tue, May 18, 2021 at 7:53 AM Michael Dewey <lists using dewey.myzen.co.uk>
> wrote:
>
>> Dear Fred
>>
>> I am not sure I understand what you are doing but the usual route if you
>> have a variable which is only meaningful in one condition is to also
>> include a two-level factor for condition.
>>
>> Incidentally if people need to use your data it is much better to
>> include it using dput() so they can read it in directly.
>>
>> Michael
>>
>> On 17/05/2021 22:50, Farzad Keyhan wrote:
>> > Dear All,
>> >
>> > My collaborators and I want to code for the "length of time" (`length`)
>> > elapsed between the last treatment and each post-test in each of our
>> > longitudinal studies (an example is below).
>> >
>> > My question is that since `length` is a moderator that only applies to
>> > "post-tests" and NOT to the "pre-tests", is it correct (i.e., from the
>> > perspective of using `length` in meta-regression) to put "0" for all
>> > "pre-test" rows (up to row # 18)?
>> >
>> > Note that "0" is a meaningful value for `length`. For example, in the
>> study
>> > coded below, "post-test 1" (i.e., time == 1) has an actual `length` of
>> "0".
>> >
>> > Thank you for your assistance,
>> > Fred
>> >                     study         mT      sdT  nT     mC      sdC nC
>> > group  length time
>> > 13   xxxxxxxxxxx    67.590 19.260 17 51.900 28.320 20           1
>>  0
>> >   0
>> > 14   xxxxxxxxxxx    67.590 19.260 17 51.900 28.320 20           1
>>  0
>> >   0
>> > 15   xxxxxxxxxxx    53.110 21.730 18 51.900 28.320 20           2
>>  0
>> >   0
>> > 16   xxxxxxxxxxx    53.110 21.730 18 51.900 28.320 20           2
>>  0
>> >   0
>> > 17   xxxxxxxxxxx    59.350 18.390 20 51.900 28.320 20           3
>>  0
>> >   0
>> > 18   xxxxxxxxxxx    59.350 18.390 20 51.900 28.320 20           3
>>  0
>> >   0
>> > 19   xxxxxxxxxxx    82.530 14.330 17 52.750 23.260 20           1
>>  0
>> >   1
>> > 20   xxxxxxxxxxx    77.500 16.070 18 52.750 23.260 20           2
>>  0
>> >   1
>> > 21   xxxxxxxxxxx    81.250 13.000 20 52.750 23.260 20           3
>>  0
>> >   1
>> > 22   xxxxxxxxxxx    82.650 15.470 17 63.900 18.890 20           1
>>  7
>> >   2
>> > 23   xxxxxxxxxxx    76.780 20.670 18 63.900 18.890 20           2
>>  7
>> >   2
>> > 24   xxxxxxxxxxx    80.050 12.090 20 63.900 18.890 20           3
>>  7
>> >   2
>> >
>> >       [[alternative HTML version deleted]]
>> >
>> > _______________________________________________
>> > R-sig-meta-analysis mailing list
>> > R-sig-meta-analysis using r-project.org
>> > https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
>> >
>>
>> --
>> Michael
>> http://www.dewey.myzen.co.uk/home.html
>>
>

	[[alternative HTML version deleted]]



More information about the R-sig-meta-analysis mailing list