Friday
Why no results in AMOS after boottraping?
You can't see AMOS output for some parts after running boottrap because they only shows up when you click in 'Estimates', scalar.
'Estimates': show results under Joint Multivariate normality assumption, while boottrap (a smaller window below the main window) should the same estimates but using different parameters calculated by running 250-2000 random samples taken from your sample.
Boottrap creates new 'critical values' for non-normal data, then uses these values to judge the null hypothesis. Under normal condition (normality), a critical value for z statistic is (-1.96: +1.96). But under non-normal condition, this technique creates creates a new 'z' and compare the obtained statistic (whatever it is) with this new one.
'Estimates': show results under Joint Multivariate normality assumption, while boottrap (a smaller window below the main window) should the same estimates but using different parameters calculated by running 250-2000 random samples taken from your sample.
Boottrap creates new 'critical values' for non-normal data, then uses these values to judge the null hypothesis. Under normal condition (normality), a critical value for z statistic is (-1.96: +1.96). But under non-normal condition, this technique creates creates a new 'z' and compare the obtained statistic (whatever it is) with this new one.
Wednesday
corr2data: Make a new var or dataset with correlations/covariance
When correlations/covariances, means or other summary statistics are the only things available. We have to make them a new variable or dataset before we do further analysis. Use corr2data in Stata 11.
I guess when one wants to recalculate published statistics, this is a way to do. Will check it again!
How to detect multivariate outliers using Mahalanobis distance?
Easy! Open data by Stata 11. Then
biplot x1 x2 x3 x4 x5, maha
A nice graph appears, with observations being scaled from +3 to –3 on both x and y axes. Observations that are above +3 and less than –3 are outliers!
Next step: Delete them!
Rudyanto: Handling Non-Normal Data in SEM
This is very good post on handling non-normal data. I helped me with my own CFA model!
Saturday
Many tools to for sample size determination
This is, http://statpages.org/, provides many tool for sample size! Note that at the middle of the page is a tool for logistic regression!
In many cases, information from previous studies (or a pilot study) are very important to determine sample size.
In many cases, information from previous studies (or a pilot study) are very important to determine sample size.
Friday
Self training multi- modelling & Package to deal with Missing Data :)
Go to this site and register a FREE course on multi-modelling ! All materials are downloadable. See guides to get MLwin for members of UK universities. Go through modules 1-3 to get basics of statistics. Look at the full list of books for multi-modelling.
Note that multi modelling can be done with many packages, including Stata!
http://www.bristol.ac.uk/cmm/learning/course.html#pay
http://www.bristol.ac.uk/cmm/software/mlwin/ordering/ac-uk.html
In order to deal with missing data (2 -level missing data), go to this website, the package is freely available:
http://www.bristol.ac.uk/cmm/software/realcom/imputation.html
Note that multi modelling can be done with many packages, including Stata!
http://www.bristol.ac.uk/cmm/learning/course.html#pay
http://www.bristol.ac.uk/cmm/software/mlwin/ordering/ac-uk.html
In order to deal with missing data (2 -level missing data), go to this website, the package is freely available:
http://www.bristol.ac.uk/cmm/software/realcom/imputation.html