FAQs on the coding template for meta-analysis
Lev3: STUDY
What if I have more than one treatment?
Does an orthogonal design of 2x2x2 require treatment variables or one with eight values?
If you have three binary variables in your design, you need to have three study (or sample,
if for example participant sex is one factor) variables describing these factors. For each
of the eight possible combinations of the variable values, we ideally have one row on the
level of the outcomes.
A minimal example:
t_therapy (1 - Cognitive, 2 - Behavioral) |
t_therapist (1- male,2 - female) |
t_length (duration therapy: 1 - 2 months,2 - 6 months) |
o_yi Outcome (for example mean score of the group) |
---|---|---|---|
1 | 1 | 1 | 8,5 |
2 | 1 | 2 | 7,8 |
1 | 2 | 1 | 8,3 |
... | ... | ... | ... |
Lev2: SAMPLE
We have 8 groups- do we then specify 8 s_meanage and s_female?
Yes, the sample description then has to be done for each group.
Does the response rate refer to all data collected or only the main dependent variable?
The response rate is the share of usable questionnaires (or study information on conducted experiments) from all eligible participants invited. This might not be given in each study (for example, if participants are recruited via flyers, we do not know, how many saw the flyer and there is no number of individual contact attempts). Then, the variable is not compulsory.
Lev1: OUTCOMES
Do I specify outcome per condition/ per factor/ for the three-way interaction? What effect sizes do you want to see reported for multifactorial ANOVAs?
If your independent variables are categorical, specify separate groups differing regarding
these variables and characterize each group concerning these variables, which you have to
specify in the template. For each of the possible combinations of the variable values, we
ideally have one row on the level of the outcomes. If you want to depict interactions with
continuous independent variables, you also need to give summary information (means) for each
separate group on the continuous variable. If there is information for many samples in a
meta-analysis in the end, the continuous variable can be used as a moderator to explain
differences in the outcomes.
A minimal example:
s_female Sex (0 - male, 1 - female) |
t_therapy Therapy (1- cognitive,2 - behavioral) |
s_meanage Age(in years) |
o_yi Outcome (for example mean score of the group) |
---|---|---|---|
0 | 1 | 40,3 | 8,5 |
1 | 2 | 35,6 | 7,8 |
1 | 1 | 31,9 | 8,3 |
0 | 2 | 52,3 | 8,7 |
How do I fill in the cells for the outcomes? What information do I need to add?
My experimental design is simple: 1 IV with 2 experimental groups, between participants.
Perhaps a minimal example for the outcome-sheet with one IV (let’s assume it to be binary, e.g. medication 1 and medication 2) and 2 samples (1 for each medication) might help:
report_ID | study_ID | sample_ID | outcome_ID | o_yi (e.g. group mean on Beck Anxiety Inventory (BAI)) |
o_sei | o_ni |
---|---|---|---|---|---|---|
1 | 1 | 1 | 1 | 30,5 | 5,6 | 43 |
1 | 2 | 2 | 2 | 32,2 | 6,3 | 39 |
I have 3 continuous dependent variables measured in a 7-point Likert scale. How do i enter these?
Do I enter these outcome variables in the first section of that worksheet (Outcome
measures for two-group comparisons) as measures of quantitative variables?
And do I
delete the rest of sections/cells?
For three dependent variables, you will have three rows with three different outcome_IDs. For a two-group-comparison of continuous variables, you will need to fill in the cells shown in the example. You can delete the other cells. Of course, in this tiny example, we have only one treatment and one sample, as you can see from the IDs!
report_ID | study_ID | sample_ID | outcome_ID | o_group1 | o_m1i | o_sd1i | o_n1i | o_group2 | o_m2i | o_sd2i | o_n2i |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 1 | 1 | 1 | Control | 5,6 | 1,5 | 54 | Treat | 3,4 | 1,3 | 53 |
1 | 1 | 1 | 2 | Control | 4,3 | 1,3 | 54 | Treat | 4,2 | 1,1 | 53 |
1 | 1 | 1 | 3 | Control | 2,5 | 2,1 | 53 | Treat | 2,7 | 1,5 | 53 |
Where do we need to enter any information regarding outcome measures?
There are no blank cells where we should enter our study information.
If you have further variables, that you would like to add and that are not specified in the template, you can do the following: At first, decide at which level of analysis your variable of interest belongs and go to the corresponding tab. According to the naming convention, a variable describing the treatment will be in the tab “Lev3Treatment” and will be called “t_[variable]”. Write the variable in the first empty column. To give us an understanding of what your variable measures / means, please also describe your new variable in the “Codebook”-tab. We have added a few blank rows for each analysis level, that you may make use of.