I am currently facing a problem trying to merge and analyze two different datasets. I am confused about some points (maybe they could be really obvious, but those are giving me terrible headache). 1) When you merged two datasets (from same population collected at different times), how can I put together the variables?
For example, dataset1 n=100, dataset2 n=150; They have in commun variables "Age" and "Perception_index". In dataset3 (the new one), I am supossed to create the variable "Merged", where 0=dataset1, and 1=dataset2, now how should I ensamble age?, Do I need to put values in the same column (dataset1 up, and dataset2 down= 250 observations?), or on the contrary do I need to create two age variables (one variable with 100 data filled and 150 lost? and backwards).
2) when you finally have the variables, how could I compare them?, for instance, is "perception_index" higher on dataset1 or on dataset2?
Thanks a lot in advance
What software are you using? do you have the same individuals or are different individuals with the same variables?
Jorge, same variables different participants. For now I want to use spss, but I want to try R later.
1) I think you need to a have single variable for common variables in the merged data set. For an example you should have one "Age" variable in the merged data set. There should be some existing functionality in SPSS to help you out with this. Please check https://www.ibm.com/support/knowledgecenter/en/SSLVMB_24.0.0/spss/base/idh_idd_add_gating.html
2) There are statistical tests that you can perform to compare qualities of 2 data sets. These tests depends on whether your variables are quantitative or qualitative. This ( http://www.maths-statistics-tutor.com/two_sample_t_test_pasw_spss.php ) can be a good example for you.
Exactly. If they were the same individuals than you would do a paired analysis. In this case you simply need to add another binary variable to account for variability that may or amy not exist between the two sets of data.
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