This is just a short little note to let people know that we have compiled a page of free, research-related resources for UCLA researchers. This page can be found at http://www.ats.ucla.edu/stat/research_resources.htm . This page is actually a modification of a flier that we put together to let graduate students know about the free, research-related resources that are available to them. The flier (in .pdf form) is linked from the web page. If you know of any other research-related resources that are free and available to all UCLA researchers or to all UCLA graduate students, please email us and let us know. Research in general, and graduate school in particular, are tough enough, and a little free help is always welcome!
-crw
Friday, September 28, 2007
Tuesday, September 18, 2007
What's the meaning of this?
If you have ever wondered "what's the meaning of this?" when looking at your output, help may be on the way. We have added lots of new annotated outputs to our web site. We have also reorganized the listing of these pages to make it easier for you to find what you're looking for. We have even added an Annotated Outputs link to our home page. The analyses annotated on these pages are the same analyses that are discussed on our Data Analysis Examples pages, so you can learn about an analysis on the Data Analysis Examples page and then learn more about each part of the output on the corresponding annotated output page. If you don't see an annotated output page for a particular analysis, please check back periodically. We are continuing to add new annotated outputs (and Data Analysis Examples) pages. We hope that you find these pages useful!
-crw
-crw
Friday, August 10, 2007
Where did all the consultants go?
Consulting was closed for most of last week, and some of you may have wondered why. This wasn’t our typical end of the qaurter “dark week.” Instead, three of us (Xiao, Christine and Rose) went to the major North American gathering for our tribe, the Joint Statistical Meetings in Salt Lake City, Utah. Now, Salt Lake City in early August may not sound like paradise to everyone, but hidden away from the heat in a convention center, we enjoyed three days of learning, discussing and networking. We even got to see other statisticians dance, and we were surprised at the number who actually do so quite well.
So what goodies did we bring back to share with all of you and each other? I (Rose) took a full day course on adjusting for multiple hypothesis tests, which introduced me to a lot of new (to me) techniques for dealing with multiplicity. I still have some homework to do, but this should be really useful when working with clients who are running a large number of significance tests. Christine enjoyed talks on the use of the ACS (the American Community Survey, which is replacing the long form of the Census), methods for handling missing data in survey non-response, imputation methods in survey research, and finding out about the new features in SUDAAN 9.2 (which should be out any day now).
When asked about the conference, Xiao said, "I really enjoyed the sessions, especially some of the invited sessions, such as the session on causality, with Paul Holland, Judea Peal and Donald Rubin as the three speakers. The round table lunch with Professor James Robins from the School of Public Health at Harvard University was extremely educational and entertaining. I also enjoyed the opportunities to talk to some really awesome statisticians from SAS and Mplus. I learned a lot from them. I (Xiao) also enjoyed my little afternoon trips, such as visiting the University of Utah by tram, having a glimpse of the gleaming Salt Lake and riding the tram to Sandy, watching the great Wasatch mountains go by from afar."
So that’s where we were and what we were doing.
r.a.m.
So what goodies did we bring back to share with all of you and each other? I (Rose) took a full day course on adjusting for multiple hypothesis tests, which introduced me to a lot of new (to me) techniques for dealing with multiplicity. I still have some homework to do, but this should be really useful when working with clients who are running a large number of significance tests. Christine enjoyed talks on the use of the ACS (the American Community Survey, which is replacing the long form of the Census), methods for handling missing data in survey non-response, imputation methods in survey research, and finding out about the new features in SUDAAN 9.2 (which should be out any day now).
When asked about the conference, Xiao said, "I really enjoyed the sessions, especially some of the invited sessions, such as the session on causality, with Paul Holland, Judea Peal and Donald Rubin as the three speakers. The round table lunch with Professor James Robins from the School of Public Health at Harvard University was extremely educational and entertaining. I also enjoyed the opportunities to talk to some really awesome statisticians from SAS and Mplus. I learned a lot from them. I (Xiao) also enjoyed my little afternoon trips, such as visiting the University of Utah by tram, having a glimpse of the gleaming Salt Lake and riding the tram to Sandy, watching the great Wasatch mountains go by from afar."
So that’s where we were and what we were doing.
r.a.m.
Wednesday, June 27, 2007
Seemingly Unrelated News
The first copies of Stata 10 arrived on Monday while I was out of town. The copies for our lab and my Mac arrived on Wednesday around noon. At 3pm, a client comes into consulting who is analyzing MRI data on several different probes over 300 time points. She has been doing non-linear modeling separately for each of the probes, however, it is the same exponential model in each case. The client wants to test whether the parameters estimated by the exponential models are statistically different or not. This turns out to be a perfect job for the new nlsur (non-linear seemingly unrelated regression) command. Ten minutes of work and it is up running. Its fun to play with new toys.
pbe
pbe
Wednesday, June 13, 2007
The Best of Stata 10
Its dangerous to try to pick out the best new features of a software package before you actually get your hands on it but I'm feeling in a daring mood. I chose features that I have either been waiting for or features that will make my statistical life easier. Since I'm the Mac guy around here anything that allows me to avoid windows software will make my life easier.
First feature: Stata 10 will have a mechanism for dealing with strata with singleton PSUs. This will make life much easier because it is a common occurance among our clients.
Second feature: Stata 10 has a new command for multilevel logit models. This can, of course, already be done in -gllamm- but it be interesting to see if it runs faster and is easier to use than -gllamm-. The HLM people will be including this in their SuperMixed program that comes out in the fall.
Third feature: Stata 10 has a new exact logistic estimation command. No more having to run LogExact in windows. I hope.
Bonus feature: Stata 10 finally gets a full discriminant analysis procedure. I know this is not on top of everybody's wish list but I like discriminant analysis and find it useful in interpreting some maonva's. Further, I will get to retire my -daoneway- ado program.
So these are my pick's, what are your's?
pbe
First feature: Stata 10 will have a mechanism for dealing with strata with singleton PSUs. This will make life much easier because it is a common occurance among our clients.
Second feature: Stata 10 has a new command for multilevel logit models. This can, of course, already be done in -gllamm- but it be interesting to see if it runs faster and is easier to use than -gllamm-. The HLM people will be including this in their SuperMixed program that comes out in the fall.
Third feature: Stata 10 has a new exact logistic estimation command. No more having to run LogExact in windows. I hope.
Bonus feature: Stata 10 finally gets a full discriminant analysis procedure. I know this is not on top of everybody's wish list but I like discriminant analysis and find it useful in interpreting some maonva's. Further, I will get to retire my -daoneway- ado program.
So these are my pick's, what are your's?
pbe
Monday, June 4, 2007
Stata 10
Stata Corp announced today that it will release version 10.0 on June 25th. There was a long list of new features and analyses, many of which have been long awaited by the Stata faithful. I don't really want to get into the new stuff in this blog, instead I want to discuss how ATS Stat Consulting deals with major new software releases.
First off, I am not sure when we will be receiving our copies of the software. The timing of this release is not optimal for our organization because our fiscal year ends on June 30th and the purchasing database shuts down several weeks before that. Furthermore, once the new fiscal year starts you can't order stuff right away because all the finance and business people are involved in preparing end of year fiscal closing reports. So, I'm not sure when we will have our hands on the software.
Basically, ATS Stat Consulting looks at new versions in terms of what web pages need to be revised, new pages that need to be created, and possibly pages that need to be removed.
Let's start with revised pages. When Stata changes how an existing command works, we need to update every page that uses the command. The biggest changes in our short history occurred when Stata did a massive overhaul of the graphics commands in Stata 8. Stata 9 also required numerous revisions, due in large part to the expanded use of prefix commands. On the surface it doesn't look like Stata 10 will require as many revisions, although there are some changes in options and features for some commands.
The tricky part here is that we have to show both the old and the new until most of our users have migrated to Stata 10.
New pages are required for new commands. There are quite a few of these. In particular the new graph editor will require pages showing how it works. We will also have to develop pages and live presentations demonstrating the best features of Stata 10.
It is not a all clear as to whether many or any pages will need to be removed. I will remove pages that are related to my -daoneway- (discriminant analysis) program since Stata 10 will provide several ways of doing disciminant analysis, but they will be replaced by pages for the new built-in procedures -discrim lda- and -candisc-.
We will be so busy in July and August with all the web stuff that I will hardly have time to work on my Stata 11 wish list.
Update: 6/8/07 -- Looks like we managed to get our purchase order in just under the wire before fiscal closing. Now its just a matter of waiting for delivery.
pbe
First off, I am not sure when we will be receiving our copies of the software. The timing of this release is not optimal for our organization because our fiscal year ends on June 30th and the purchasing database shuts down several weeks before that. Furthermore, once the new fiscal year starts you can't order stuff right away because all the finance and business people are involved in preparing end of year fiscal closing reports. So, I'm not sure when we will have our hands on the software.
Basically, ATS Stat Consulting looks at new versions in terms of what web pages need to be revised, new pages that need to be created, and possibly pages that need to be removed.
Let's start with revised pages. When Stata changes how an existing command works, we need to update every page that uses the command. The biggest changes in our short history occurred when Stata did a massive overhaul of the graphics commands in Stata 8. Stata 9 also required numerous revisions, due in large part to the expanded use of prefix commands. On the surface it doesn't look like Stata 10 will require as many revisions, although there are some changes in options and features for some commands.
The tricky part here is that we have to show both the old and the new until most of our users have migrated to Stata 10.
New pages are required for new commands. There are quite a few of these. In particular the new graph editor will require pages showing how it works. We will also have to develop pages and live presentations demonstrating the best features of Stata 10.
It is not a all clear as to whether many or any pages will need to be removed. I will remove pages that are related to my -daoneway- (discriminant analysis) program since Stata 10 will provide several ways of doing disciminant analysis, but they will be replaced by pages for the new built-in procedures -discrim lda- and -candisc-.
We will be so busy in July and August with all the web stuff that I will hardly have time to work on my Stata 11 wish list.
Update: 6/8/07 -- Looks like we managed to get our purchase order in just under the wire before fiscal closing. Now its just a matter of waiting for delivery.
pbe
Sunday, June 3, 2007
More Control Groups Gone Wild
We had a client, come in to consulting recently, who was studying people receiving treatment in mental health clinics. He classified these patients into three groups; Group 1) individuals who had a personal history of depression, group 2) individuals with a family history of depression and Group 3) individuals with no history of depression. The last group was the control group. The outcome variable was a binary indicator, whether or not they had experienced a depressive episode since their last visit to the clinic.
The problem was that the control group did not experience any depressive episodes. This, in turn, creates a problem for logistic regression. There was an error message indicating that group 3 not equal zero predicts failure perfectly. And, instead of two degrees of freedom for group there was only one degree of freedom (comparing Group 1 versus Group 2) and no coefficient for Group 3 versus Group 1.
This could be dealt with by changing one response score in Group 3 at random from zero to one. There was a further complexity however. Each individual in each of the three groups was measured on 12 occasions, i.e., once a month for a year. And during those twelve months none of the individuals in the control group ever experienced a depressive episode. Since change over time was one of the research questions, it didn't seem right to randomly chance responses in the control group to one.
In the end, there just wasn't not any useful information available from Group 3. It was clearly one more case of control groups gone wild.
pbe
The problem was that the control group did not experience any depressive episodes. This, in turn, creates a problem for logistic regression. There was an error message indicating that group 3 not equal zero predicts failure perfectly. And, instead of two degrees of freedom for group there was only one degree of freedom (comparing Group 1 versus Group 2) and no coefficient for Group 3 versus Group 1.
This could be dealt with by changing one response score in Group 3 at random from zero to one. There was a further complexity however. Each individual in each of the three groups was measured on 12 occasions, i.e., once a month for a year. And during those twelve months none of the individuals in the control group ever experienced a depressive episode. Since change over time was one of the research questions, it didn't seem right to randomly chance responses in the control group to one.
In the end, there just wasn't not any useful information available from Group 3. It was clearly one more case of control groups gone wild.
pbe
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