Jump to content
Sign in to follow this  
karen1204

Quantitative Psychology / Educational Measurement Fall 2014 SOP help

Recommended Posts

Hi everyone,

I am applying applying to Quantitative Psychology and Educational Psychology programs which offer a Quantitative Methods concentration. The schools I will be applying to are UC Berkeley, UCLA, USC,

UC Riverside, UI- Chicago, University of Washington - Seattle, Fordham University, Rutgers - New Brunswick, and CUNY Graduate Center (but for CUNY this will be I/O Psych, because I've been working with a professor in Baruch for almost two years and got familiar with the program).

I have a BA in psych, have 2+ years of research experience, worked on 3 projects ( 1 of which was my own independent project as part of NSF's REU program), was a TA for an undergrad psych stats course for one semester, audited for a doctoral level Psychometrics course, and have job experience working with youth. My mentor has stated that my experience should give me a good shot at in applying to quant programs.

However, I'm worried about my chance in these programs, mainly because I do not have an extensive math or stats background. I am stuck right now at writing up a strong statement of purpose, because I don't know how broad or specific I should define my research interests. My mentor says given that I do not have a math or stats background, the grad admission committee should understand, and that I can broadly define my research interests. My interest in statistics developed when I was a TA for psych stats. But undergrad stats only taught up to ANOVA, linear regression, and chi square. I am currently learning advanced stats tests on my own, like logistic regression and factor analysis. i have a book that teaches me stats using SPSS and the R.

As for research interests, I am interested in test validity and using cognitive diagnosis models to do this. My experience working with youth led me to take great interest in testing. I'm particularly interested in how covariates like SES, gender, or race can have an effect on educational outcomes. does this "make sense" or is it "good enough" to be in a SOP? I am very excited to find a field that can combine my interests stats and education.

I've looked up the publications of the faculty in the programs I'm applying, but I cannot say I understand these articles completely, since it requires advanced training in stats, so it's especially hard to determine which faculty I would like to work with.

Can anyone give me some guidance? Thank you so much for reading! Any advice is appreciated!

Share this post


Link to post
Share on other sites

Given what you want to do, I think Ed Psych will work better for you than Quant. If your focus is more on the outcome than it is on the stats (and I'm not knocking stats, don't get me wrong, I'm a Statistical Analyst), then Ed Psych is the way to go. 

Share this post


Link to post
Share on other sites

As for research interests, I am interested in test validity and using cognitive diagnosis models to do this. My experience working with youth led me to take great interest in testing. I'm particularly interested in how covariates like SES, gender, or race can have an effect on educational outcomes. does this "make sense" or is it "good enough" to be in a SOP? I am very excited to find a field that can combine my interests stats and educatio

 

if these are your research interests then ditch Quant Psych and go for Ed Psych all the way. I've worked in the quantitatively-oriented educational measurement program from my University and i'd say your research interests are just right in line with the assessment people rather than the quant analysis people. 

 

and for programs as such, you don't need to have a heavy background in Statistics. i think with your usual upper-level methods stats course should be more than enough. but if you've audited a doctoral course AND TA'ed an undergrad stats course i'd say you've demonstrated more than enough proficiency in the area to be a qualified candidate. 

 

all the math/stats/programming experience you need you'll learn along the way.

Share this post


Link to post
Share on other sites

You don't need a very extensive math or stats background for quant psychology.  You just need to show interest.  I am doing a quantitative postdoc next year and one of the directors has a PhD in quantitative psychology; she said when she got there, she had taken one statistics class and no calculus.  I would say more competitive applicants have probably had an advanced statistics class and 2 or 3 semesters of calculus, but plenty of quant psychology students go in with a psych major and little math.  You can always take the classes when you are in your graduate program, if you need them.

You may also want to check out UNC-Chapel Hill (quantitative psychology) and Penn State University (human development and family studies; they have a pretty strong quantitative core and you can earn an MAS in applied statistics along with your PhD.  They also have a methodology training predoc).   NYU also offers a quantitative minor.  Here's a list in case you need one: http://www.apa.org/research/tools/quantitative/index.aspx?item=2

If I could go back in time, quantitative psychology is the PhD I would've gotten.  I didn't know about the subfield when I was in college!

If your focus is more on the outcome than it is on the stats (and I'm not knocking stats, don't get me wrong, I'm a Statistical Analyst), then Ed Psych is the way to go. 

Well, most quantitative psychologists have substantive interests as well as methodological and statistical interests.  I agree that if you are not at all interested in statistical model/test development as well as outcomes, then quant psych may not be right for you, but if you're interested in both a quant psych department still may suit you well.  Also, quant psychs do measurement and test validity research as well - psychometrics is definitely one component of quantitative psychology.

Share this post


Link to post
Share on other sites

Thanks for all the feedback, everyone!

I would say that I am interested in both, educational outcome + statistical modeling. However, how broadly or specifically should I define my research interests in my statement of purpose? Would writing covariates affecting educational achievement be too broad? I was told by my professor that I should also write about my quant interest in my research interests section.

I'm trying to write the same paragraphs about how I developed interest in the quant field and what I did as an undergrad, and tweak the last paragraph where I talk about my research interest for each program. The tough part is to add some "quant" element into my research interests - especially in essays for the strictly quant psych programs, not the Ed psych programs. I've read some papers written by professors in the programs I'm applying. For the most part I understand what they're talking about when the articles are about things like Rasch model, longitudinal data in high schoolers etc but am floored when they write articles that are strictly about statistical models, as I don't have that kind of training yet...

Any advice on this? Or how did you all write your statement of purpose? Thanks again for reading!

Share this post


Link to post
Share on other sites

I don't think the phrase "covariates affecting educational achievement" is too broad, per se, but it speaks more to Ed Psych. A Quant focus would be something more like "mathematically modeling the relationship between a number of covariates and educational achievement," or something to that effect. It's the focus on the covariates versus the math.

 

What specific quantitative techniques are you interested in?

Share this post


Link to post
Share on other sites

For the most part I understand what they're talking about when the articles are about things like Rasch model, longitudinal data in high schoolers etc but am floored when they write articles that are strictly about statistical models, as I don't have that kind of training yet.

 

 
Lisa44201 is right. why don't you maybe give us a reference of some article of these professors to get an idea of what kind of models you're interested in?
 
when i wrote my statement i just lumped everything together in having a "keen interest in latent variable modelling" whatever that was supposed to mean. 
 
it got me in so i guess it can't be that bad? lol

Share this post


Link to post
Share on other sites

Ok will do... I am currently working on the NSF application, applying for quant psych field of course. I have to submit two essays 1. Personal statement + research experience 2. My graduate research topic and my approach

I don't have trouble with the first essay. Still finishing that up. But the second one I will have some major issues with, since I have to formulate a concrete research topic. I am hoping the committee will take into account that my background was not in stats?

Ok some of the articles I have are:

Factors Affecting the Item Parameter Estimation

and Classification Accuracy of the DINA Model

By Jimmy de la Torre (Rutgers)

Comparing longitudinal profile patterns of Mathematics

and Reading in early child longitudinal study, kindergarten:

The Profile Analysis via Multidimensional Scaling (PAMS)

approach

By Se-Kang Kim (Fordham)

Recruiting, Preparing, and Retaining

High Quality Secondary Mathematics

and Science Teachers for Urban Schools:

The Cal Teach Experimental Program

by XiaoXia Newton (UC Berkeley)

A Model of Cognition: The Missing Cornerstone

of Assessment by Mark Wilson (also from UC Berkeley) I've downloaded many of Dr. Wilson's articles but just found out that he's not serving as an adviser for any new students (sad, since I really liked the research he's doing)

I really really appreciate all the feedback. I've never been so lost at words in writing up an essay about myself. I can describe how I got into stats and all but it's just the research interest part that is hindering me from finishing.

May I also message you guys my SOP once I'm finished? As well as my NSF essays? Thank you so much!

Share this post


Link to post
Share on other sites
well, your first article (De la Torre) deals with Item Response Theory (a *must* in Psychometrics for Education but not necessarily as popular among Quant Psychs), dwelling particularly on Bayesian estimation. the Bayesian approach to data analysis is super hot-hot-HOT now among social sciences but it can be opposed by hard-line frequentists, so it really depends on whether the person you'd like to wrok with is a frequentist or Bayesian. a good friend of mine who works with Herb Marsh (one of the best in our field) once said to me something along the lines that if you submit a manuscript for publication with the words "Bayesian" or "Markov Chain Monte Carlo" on it, your chances of publishing go up significantly among quant journals. it turned out to be true for me, so i jumped in that bandwagon. it may not be yours, but you can always say you have an "interest" in Bayesian modelling. 
 
you may want to say something about having an interest in Simulations (as in Monte Carlo simulations) and you're eager to learn new software that enabales this (people like Mplus or R which is rapidly becoming, as the New York Times phrases it the "lingua franca" of data scientists). 
 
you could say that maybe you have some project that uses longitudinal data and you're interested in either using multi-level models or structural equation modelling (SEM) to tackle it becuase you've heard it's the correct way to go about these things. i like the Kim article you mentioned where they use Multi Dimensional Scaling because i don't see that used very often for longitudinal data analysis. i'm more familiar with it being approached from a latent growth curve perspective.
 
i can't really help you with the other two articles because it seems like their more assessment-oriented rather than stats-oriented, and that's not my area of expertise.
 
just keep in mind that you are not expected to know ANY of this stuff. you're going to gradschool to learn it, plus it depends on the prof you may want to work with. even though my uni has a small Quant Psych program, for instance, the profs in it are diametrically different in the type of grad student they want. Prof A is happy to get people who are enthusiastic (and obviously numbers-savvy) because he'll teach them the rest. Prof B doesn't like to take in anyone who doesn't have any previous programming experience and a BSc, which guarantees said candidate took at least some math beyond Grade 12.
 
in general,  you just have to show that you feel comfortable-enough around Statistics to learn more about them.
 
overall i'd maybe just touch on three main points:
 
( a ) you're interested in latent variable models (structural equation modelling, item response theory, etc. all fall under this umbrella)
 
( b ) you're OK with expanding your knowledge as far as software goes... maybe in going beyond GUI-heavy (Graphic User Interface) programs like SPSS, Minitab or JMP and working more in a syntax/programming-only environment 
 
( c ) you're open to learn about statistics.
 
everything else will fall in its place. 
Edited by spunky

Share this post


Link to post
Share on other sites

 

 
overall i'd maybe just touch on three main points:
 
( a ) you're interested in latent variable models (structural equation modelling, item response theory, etc. all fall under this umbrella)
 
( b ) you're OK with expanding your knowledge as far as software goes... maybe in going beyond GUI-heavy (Graphic User Interface) programs like SPSS, Minitab or JMP and working more in a syntax/programming-only environment 
 
( c ) you're open to learn about statistics.
 
everything else will fall in its place. 

 

Even though this post wasn't directed at me, it was so helpful and uplifting!

 

I have a lot of experience with a technique known as integrative data analysis (i.e. pooling data across studies), and am currently learning how to write syntax in Mplus for SEM (along with already being skilled in writing syntax in SPSS). Since I have such specific experience though, it's been a little tricky for me to talk about other aspects of quant. in my personal statements. Your post has brought me back down to Earth though, so thank you!

Share this post


Link to post
Share on other sites

Even though this post wasn't directed at me, it was so helpful and uplifting!

 

I have a lot of experience with a technique known as integrative data analysis (i.e. pooling data across studies), and am currently learning how to write syntax in Mplus for SEM (along with already being skilled in writing syntax in SPSS). Since I have such specific experience though, it's been a little tricky for me to talk about other aspects of quant. in my personal statements. Your post has brought me back down to Earth though, so thank you!

 

well, in my opinion, if you're already doing IDA chances are you're already pretty advanced in your stats. besides, with the advent of this overload of info, people who are proficient in meta-analysis, IDA, big data analytics, etc. are a hot, hot asset. 

 

i'm currently part of a research team that does text analysis in educational policy (so tracking and measuring trends among thousands and thousands of pages from published articles related to it) and we have the equivalent of 11 King James Bibles worth of content. who's ever gonna read through that!? QUANTS TO THE RESCUE!!!! :D

Share this post


Link to post
Share on other sites

Whewww, seriously feeling much much better!

 

That's awesome you are doing text analysis research! It is such a powerful and useful tool, especially when talking about 11 King James Bibles worth of content ;) Quants to the rescue indeed! What kind of questions are you studying using the text analysis?

 

Have you checked out all the text analysis research going on with social media? There's some pretty cool stuff, and really cool ways to leverage and combine multiple data sources such as linking Twitter with CDC county level data. This team is one example: http://wwbp.org/

Share this post


Link to post
Share on other sites

That's awesome you are doing text analysis research! It is such a powerful and useful tool, especially when talking about 11 King James Bibles worth of content ;) Quants to the rescue indeed! What kind of questions are you studying using the text analysis?

 

Have you checked out all the text analysis research going on with social media? There's some pretty cool stuff, and really cool ways to leverage and combine multiple data sources such as linking Twitter with CDC county level data. This team is one example: http://wwbp.org/

 

 

well, we're being led by a professor and his students who are interested in seeing how the narrative around educational policy has been changing since around the 70s until now. something about the laws changing to favour the rich over the poor (no surprises there, lol) under Bush I and Bush II. 

 

what i found more appealing (because i honestly find politics a tad bit boring) is the approach. the two quants in our group who do text analysis are coming up with the matrices of measures so that the other SEM modeler out there, with me, can fit a latent growth model. my guess is that once all the text analytics are gathered (mostly classical latent semantic analysis) they'll pass their resultsto the other quants (us) who will fit the latent trajectories to see how these concepts (like "fairness" or "equality" in education) change over time.

 

i was drawn to it because i found the appeal unique. i have never seen people try to do SEM on text analyses but, once you start thinking about it, it makes perfect sense. just as people who can do meta-analysis also using SEM or multilevel models.

 

what are you doing IDA for?

Edited by spunky

Share this post


Link to post
Share on other sites

A little bit late, but if you can freely talk about the underlying logic of statistical models/formulas in relations to the structural integrity of the psychological phenomenon in focus, then you should be fine :)

 

Good Luck!

Share this post


Link to post
Share on other sites

Hi all,

 

thank you for all the feedback. It has been a while since I responded. I've been working on my personal statement, but alas I am finished. Basically since I have had no intensive training in statistics, I just wrote an honest essay how I found quantitative methods, how it changed my perspective on psychology (I included how i initially wanted to be a clinical psychologist to understand the human expereince and alleviate human suffering), and through being a TA and RA I learned that quant psych could indeed perform the same mission. Therefore I would like to further my training in the respective quant program.

 

But for my research interests, I'm not sure if this is good enough for a quant program:

 

"...Broadly, I am interested in studying psychological measurement, longitudinal methods and developmental changes. I am particularly interested in how acculturation levels account for differences in psychological well-being and academic performance over time for minority youth. I am also interested in the relationship between acculturation and social behavior, such as drug abuse and gambling, which are prevalent issues among the immigrant population. Furthermore, I hope to study latent variable models to tackle these research topics. "

 

 

Then after this I wrote about why I would be a great fit to work with Prof A and B, why I want to study in their program, how I will prepare for grad school by familiarizing myself with the R, taking linear algebra and calculus courses before beginning grad school, and then my short term and long term goals.

 

One more thing** I explained in one sentence about my GRE score (V. 152 Q. 155. The comparable chart shows on the old scale it's somewhere V. 490 Q.700-710), that standardized testing is my Achilles' heel but my past academic record should be more indicative of my graduate ability.  I did this because my GRE is considered mediocre/average for some of the more prestigious programs I'm applying to like UCLA, who listed that their average applicants have GRE scores in the 80th or 90th percentile. Do you think it is necessary to explain this? Or should I leave it out? How important are GRE scores for quant programs? 

 

Any feedback would be helpful! Thanks and happy holidays! :)

Edited by karen1204

Share this post


Link to post
Share on other sites

well, we're being led by a professor and his students who are interested in seeing how the narrative around educational policy has been changing since around the 70s until now. something about the laws changing to favour the rich over the poor (no surprises there, lol) under Bush I and Bush II. 

 

what i found more appealing (because i honestly find politics a tad bit boring) is the approach. the two quants in our group who do text analysis are coming up with the matrices of measures so that the other SEM modeler out there, with me, can fit a latent growth model. my guess is that once all the text analytics are gathered (mostly classical latent semantic analysis) they'll pass their resultsto the other quants (us) who will fit the latent trajectories to see how these concepts (like "fairness" or "equality" in education) change over time.

 

i was drawn to it because i found the appeal unique. i have never seen people try to do SEM on text analyses but, once you start thinking about it, it makes perfect sense. just as people who can do meta-analysis also using SEM or multilevel models.

 

what are you doing IDA for?

 

That sounds really cool! Text analysis is becoming a very lucrative tool for gaining psychological insights in a more objective fashion. It's also a really cool form of big data. 

 

Our IDA projects center around understanding the associations between factors that lead to psychological well-being in adolescence and prospective health behaviors and health outcomes in mid-adulthood and later adulthood. In a nutshell, we are trying to build the literature on how psychological well-being is associated with physical health across the lifespan. For example, one project I'm keen on is using 7 datasets to look at whether perseverance at age 16 is related to 7 different health behaviors and indicators at age 30, and health outcomes such as cardiovascular disease at age 50.

 

Also, on a bright note, I have finally submitted all of my apps! One step closer to that PhD... =)

Share this post


Link to post
Share on other sites

Create an account or sign in to comment

You need to be a member in order to leave a comment

Create an account

Sign up for a new account in our community. It's easy!

Register a new account

Sign in

Already have an account? Sign in here.

Sign In Now
Sign in to follow this  

×

Important Information

By using this site, you agree to our Terms of Use and Privacy Policy.