Hi,
My study:
- 2 groups- 1. Not allowed to work; 2. Allowed to work (control)
- compare the groups on various aspects like quality of life, depression, anxiety, etc on standardized quantitative questionnaires
- compare if coping ability (2 standardized quantitative scales) predict scores on above measures
Currently I'm running preliminary analysis on collected data (n=103+) which is still ongoing. Have checked for normality.
Some questionnaires' data was normal, on others it wasn't:
Questionnaire 1- normally distributed; Skewness- normal but negative; Kurtosis- normal but negative
Quest. 2- not normal; skew- normal but negative; kurtosis- negative and not normal (more than 1.96)
quest. 3- not normal; skew- positive; kurtosis- normal
quest. 4- not normal; skew- positive; kurtosis- normal
quest. 5- not normal; skew- positive; kurtosis- not normal
quest. 6- not normal; skew- negative but normal; kurtosis- negative but normal
quest. 7- normal; skew-negative but normal; kurtosis- negative but normal
quest. 8 (can be ignored as of now as not sure of scoring)- normal, skew- negative but normal; negative but normal
so, it's quite a mix of normally and not-normally distributed data. i went ahead and did log transformation and it didn't help much- varied result once again.
I also later realized I had done it wrong as I didn't account for negative skewness of some questionnaires.
Also, some questionnaires have 'zero' values as well.
My questions now:
1. Do I need to transform data?
2. How do I transform it, given negative skewness on some questionnaires (Andy Field doesn't go into much detail on this in his book
i.e. using SPSS)
3. Would the same procedure be used for all questionnaires given the variety of results- positively skewed-kurtosis/negatively skewed-kurtosis/ not skewed-kurtosis?
Please help!
My study:
- 2 groups- 1. Not allowed to work; 2. Allowed to work (control)
- compare the groups on various aspects like quality of life, depression, anxiety, etc on standardized quantitative questionnaires
- compare if coping ability (2 standardized quantitative scales) predict scores on above measures
Currently I'm running preliminary analysis on collected data (n=103+) which is still ongoing. Have checked for normality.
Some questionnaires' data was normal, on others it wasn't:
Questionnaire 1- normally distributed; Skewness- normal but negative; Kurtosis- normal but negative
Quest. 2- not normal; skew- normal but negative; kurtosis- negative and not normal (more than 1.96)
quest. 3- not normal; skew- positive; kurtosis- normal
quest. 4- not normal; skew- positive; kurtosis- normal
quest. 5- not normal; skew- positive; kurtosis- not normal
quest. 6- not normal; skew- negative but normal; kurtosis- negative but normal
quest. 7- normal; skew-negative but normal; kurtosis- negative but normal
quest. 8 (can be ignored as of now as not sure of scoring)- normal, skew- negative but normal; negative but normal
so, it's quite a mix of normally and not-normally distributed data. i went ahead and did log transformation and it didn't help much- varied result once again.
I also later realized I had done it wrong as I didn't account for negative skewness of some questionnaires.
Also, some questionnaires have 'zero' values as well.
My questions now:
1. Do I need to transform data?
2. How do I transform it, given negative skewness on some questionnaires (Andy Field doesn't go into much detail on this in his book
i.e. using SPSS)3. Would the same procedure be used for all questionnaires given the variety of results- positively skewed-kurtosis/negatively skewed-kurtosis/ not skewed-kurtosis?
Please help!
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