Post by mt on Jul 25, 2019 14:07:49 GMT
The original paper says the following:
"The phenotypes were corrected for age and sex, and standardized to z-scores in each adult and adolescent data set separately. We used a two-tailed 90% Winsorisation to adjust the z-scores of four individuals in the adult data set with absolute values greater than 4.17, the (100 − 5/3248)th percentile of the standard normal distribution based on Bonferroni correction..."
How should phenotypes and/or continuous covariates be preprocessed for GREML analysis?
- Should I Z-score normalize phenotypes/covariates?
- I want to correct for Age and Sex - should I do this manually on the phenotypes, or is it sufficient to include these variables as covariates?
"The phenotypes were corrected for age and sex, and standardized to z-scores in each adult and adolescent data set separately. We used a two-tailed 90% Winsorisation to adjust the z-scores of four individuals in the adult data set with absolute values greater than 4.17, the (100 − 5/3248)th percentile of the standard normal distribution based on Bonferroni correction..."
How should phenotypes and/or continuous covariates be preprocessed for GREML analysis?
- Should I Z-score normalize phenotypes/covariates?
- I want to correct for Age and Sex - should I do this manually on the phenotypes, or is it sufficient to include these variables as covariates?