Friday conference highlights
Wow! Howdy flist! I'm back at my hotel now and perhaps you might guess by the number of exclamation points that I've had two drinks! :D
Today was one of those days that reiterates the good things about going to conferences.
To start, I went to a presentation on software called Mplus and the presenters were SUCH lovely people. Funny, energetic, one of them saw me drinking a cup of tea and joked "You'd better get a coffee dear. This is a presentation on statistical software." LOLOL
As it turns out, Mplus offers exactly what I'm looking for to analyze my data set* and now I'm all juiced up in my mental pants. I put my business card in their box for a chance to win a copy of the software, but a friend of mine from my program has offered to give me her copy of the previous version and a tutorial on Structured Equation Modeling**. I am also set to sit down with renowned zombie statistician Robert Smith? at Gallifrey to further discuss SEM. I AM SO PSYCHED TO DO MY DATA ANALYSIS NOW IT'S NOT EVEN FUNNY.
At lunch I caught up with a former fellow student who is now working at a University, and saw a few other fellow candidates. I also went to the LGBT caucus, which was a bit of a snoozeville. But I ran into that assistant professor I met at the other conference who wanted my syllabi on LGBT policy and he gave me a new idea for possible theory for my dissertation! He also briefly discussed with me some data he collected that might be fruitful for a joint paper.
And then this evening was the conference reception. Free dinner! Free drinks! I was flirted with by TWO different women! And in casual chatting with one of the faculty at my university, she gave me the idea to submit an article for a content analysis of literature review based on what I wrote for the Williams Institute grant I applied for. So even though I didn't get that grant, I can recycle what I wrote and tweak it for a possible publication!
The nerdy. It feels soooo good right now.
* Mplus allows you to three things I find interesting - structured equation modeling (SEM), Exploratory Factor Analysis (EFA), and Latent Class Analysis (LCA)
** SEM allows you to combine multiple observed variables to create a combined variable. So for example, I want to look at the combined effect of gender presentation, being out and documentation status (whether someone has changed documents to reflect identified gender and name change) on income, employment discrimination and the decision to not file a formal complaint for employment discrimination. EFA allows you to throw in a mixed bag of variables and see if any relationships emerge. LCA allows you to do this as well, only with the specific focus of examining heterogeneity within groups (e.g. among those who have Bachelor's degrees, or among people of color).
Today was one of those days that reiterates the good things about going to conferences.
To start, I went to a presentation on software called Mplus and the presenters were SUCH lovely people. Funny, energetic, one of them saw me drinking a cup of tea and joked "You'd better get a coffee dear. This is a presentation on statistical software." LOLOL
As it turns out, Mplus offers exactly what I'm looking for to analyze my data set* and now I'm all juiced up in my mental pants. I put my business card in their box for a chance to win a copy of the software, but a friend of mine from my program has offered to give me her copy of the previous version and a tutorial on Structured Equation Modeling**. I am also set to sit down with renowned zombie statistician Robert Smith? at Gallifrey to further discuss SEM. I AM SO PSYCHED TO DO MY DATA ANALYSIS NOW IT'S NOT EVEN FUNNY.
At lunch I caught up with a former fellow student who is now working at a University, and saw a few other fellow candidates. I also went to the LGBT caucus, which was a bit of a snoozeville. But I ran into that assistant professor I met at the other conference who wanted my syllabi on LGBT policy and he gave me a new idea for possible theory for my dissertation! He also briefly discussed with me some data he collected that might be fruitful for a joint paper.
And then this evening was the conference reception. Free dinner! Free drinks! I was flirted with by TWO different women! And in casual chatting with one of the faculty at my university, she gave me the idea to submit an article for a content analysis of literature review based on what I wrote for the Williams Institute grant I applied for. So even though I didn't get that grant, I can recycle what I wrote and tweak it for a possible publication!
The nerdy. It feels soooo good right now.
* Mplus allows you to three things I find interesting - structured equation modeling (SEM), Exploratory Factor Analysis (EFA), and Latent Class Analysis (LCA)
** SEM allows you to combine multiple observed variables to create a combined variable. So for example, I want to look at the combined effect of gender presentation, being out and documentation status (whether someone has changed documents to reflect identified gender and name change) on income, employment discrimination and the decision to not file a formal complaint for employment discrimination. EFA allows you to throw in a mixed bag of variables and see if any relationships emerge. LCA allows you to do this as well, only with the specific focus of examining heterogeneity within groups (e.g. among those who have Bachelor's degrees, or among people of color).