tag:blogger.com,1999:blog-6710487119650146215.post7132514397911690982..comments2017-06-14T22:46:43.010-07:00Comments on R Tutorial Series: R Tutorial Series: Hierarchical Linear RegressionJohnhttp://www.blogger.com/profile/05331039307550313006noreply@blogger.comBlogger7125tag:blogger.com,1999:blog-6710487119650146215.post-36803272739300961542014-10-02T03:16:31.700-07:002014-10-02T03:16:31.700-07:00First, thanks for the tutorial.
Good to know that ...First, thanks for the tutorial.<br />Good to know that I did go in the right direction. But I have a question: With non-complete data I have the problem that I can not do it this way because each regression model than have different cases excluded because of the different missing patterns. So is there a way, besides multiple imputation, to compare different models in a hierachic regression with non-complete data?<br />Thanks for any comments.<br />emotionsloshttp://www.blogger.com/profile/07510857757112169855noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-19430306939267247392012-06-27T08:22:04.262-07:002012-06-27T08:22:04.262-07:00The comments above refer to the title of post, whi...The comments above refer to the title of post, which was originally wrong, and not to the content.<br /><br />I disagree about your thought that this is like stepwise regression. In HLR, the researcher decides upon the order of a few variables and examines them sequentially in a few models. In stepwise regression, a computer iterates through all possible variable combinations in every model. If you search Google on this topic and you will find similar, but more extensive comparisons.John Quickhttp://www.blogger.com/profile/05331039307550313006noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-60463913384681724892012-06-26T21:37:09.291-07:002012-06-26T21:37:09.291-07:00Agree with the comments above. This seems to be ma...Agree with the comments above. This seems to be manual approach to step-wise regression which has numerous problems.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-59655606350070355942010-07-09T08:54:33.389-07:002010-07-09T08:54:33.389-07:00Thanks for the comments. I updated the tutorial to...Thanks for the comments. I updated the tutorial to reflect the appropriate title.John M. Quickhttp://www.blogger.com/profile/05331039307550313006noreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-88815842328469459842010-07-09T05:23:57.134-07:002010-07-09T05:23:57.134-07:00Indeed, you are discussing what is known as "...Indeed, you are discussing what is known as "Hierarchical regression". The term "Hierarchical linear modeling" (or HLM) is used for multilevel models and using that as a title for this part is confusing.<br />Apart from that, it is nicely done.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-85154809334156670342010-07-03T06:06:48.142-07:002010-07-03T06:06:48.142-07:00Just a doubt:
Your title "Hierarchical linea...Just a doubt:<br /><br />Your title "Hierarchical linear modeling" is suggestive of mixed modeling/HLM/MLM literature (used for clustered/non-independent data), and not the hierarchical regression (based on analyzing hierarchical Anova models) that you actually seem to be explaining here. <br /><br />Maybe my mistake (i AM a novice), but if what i say is true, i guess it may be better to correct this and restate the title as "Hierarchical regression"; otherwise new-comers interested in mixed modeling might mistake the message.<br /><br />Bye,take care.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-6710487119650146215.post-36574639238953069912010-06-25T02:19:47.281-07:002010-06-25T02:19:47.281-07:00How do handle categorical independent variables in...How do handle categorical independent variables in HLM?Anonymousnoreply@blogger.com