The software interface was discussed in the previous article: Introducing Comprehensive Meta analysis (CMA) software. To calculate the effect size, one needs to enter the data into specific data entry formats. This article will acquaint the user with the procedure of entering the data into the software.
Selecting the data entry format in CMA
This article will take the procedure up from the quick options toolbar. The toolbar offered the Insert column for effect size data option. This option takes the user to Insert columns for effect size data dialog box. This will further take to different data entry formats directory. The data entered in columns is referred to as column for effect size data. The spreadsheet is created after selection of appropriate data entry format. Simply click Insert column for effect size data icon on the toolbar, or follow Insert à Effect Size data option. Next step is to proceed to select the desired data entry format.
Upon selecting the Effect Size data option, the software will offer a Welcome dialog box. Select Next, to open second dialog box, designated as Types of studies included. After selecting appropriate category user can enter data as per the experimental design.
Note: Different clinical studies follow different study designs such as randomized control trials, cohort studies, cross sectional studies.
Data entry formats as offered by different categories
Shown below are the different data entry formats with further subdivisions into different sub-groups:
1. Studies reporting comparisons: Includes data entry formats, with respect to the comparison of two different groups, time points or exposures. These formats pertain to the experimental design involving the comparison between two groups, time points or exposure conditions. The data belonging to a different type of formats such as continuous, binary or correlations, can serve as indices/measures.
For example: If the user enters the continuous data involving the mean and standard deviation from different treatment groups. Then, the software computes standardized mean difference as effect size.
The dichotomous data involves discreet data pertaining to two distinct categories, such as responders and non-responders of a treatment. On the other hand, continuous data includes the data measures on a continuum, which in case of treatment effect includes data for means, standard deviation.
2. Studies reporting estimates for one group or a single time point: CMA provides options for performing meta-analysis of the studies involving a single group. Correspondingly, the format of experimental design tends to focus on variables like mean, proportion or rates. This is in case of a single group or a single time point.
For example: The user can enter discreet dichotomous data for number of events and samples size, and mean values for continuous data.
3. Studies reporting generic data: CMA is further used to analyze data related to generic point estimates, in raw units and as log scales. Point estimates in clinical trials refer to the single number data summarizing the results from the trial. These include; odds ratio, risk ratio, or risk difference.
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