Left Skew

Hey AppliedCogPsych,

You may have the credentials to apply to a single school and get accepted into that school (LA Tech) but I would definitely look more into where you can find a professor that fits your goals. I feel like you may be interested in Quantitative Psych and Measurement as well. I've attached a list of programs that may align with what you want to do. If you have the resources, apply to more than 1 program.

1) I can't speak to this directly, you may want to reach out to a student with similar interests currently in the program.
2) I/Os tend to have few true quant professors in the departments, so keep this in mind when looking for research support. Big areas in the field: Psychometrics, automation, statistical computing/programming, gamification. Coming from cog/neuro I feel you will have a novel perspective. A lot of companies are creating assessments, simulations, and games to hire people, but have they validated the cognition used in their assessments? I/Os love to measure cognitive constructs but may struggle with their behavioral manifestations (e.g., Employee Engagement- just because I say I'm engaged doesn't mean I'm showing up to work early every day). 

3) You have your M.S. in Cog/Neuro so you will already be unique. If you can get some I/O related research on your CV you'll be set. Send emails to professors asking if they need help coding or running participants, this will help you. I'm also a big proponent of gaining a working-knowledge of R. You can go to SIOP or regional conferences to get your name out there.

4) I took some time off and am currently working. I got my MS in I/O and now I'm going back for my doctorate (starting in the Fall). Thus, I can't speak to a doctoral level position but I consider my current role similar in terms of what I do, maybe not so similar in terms of pay. There is actually an I/O PhD that has the same job title as I do, and I'm the most tenured in a department of solely PhDs. Pay is only the real difference and maybe professional growth. However, I work in psychometrics for a medium-sized credentialing company. So I/Os can get in so many areas: Testing, HR, even Data Science, it's all how you market yourself. 

Let me know if you have any more questions.

 
 
IOStatsMeasProgramList.csv

This happens in academia far too often. You could have near-perfect GRE scores, GPA, letters of recommendation, and even fit; yet you're still not selected. Social capital is a powerful thing, I wish there was more research on it. I worry when applying to programs that also have a terminal masters because of how often schools transition (though deserving) students from the masters to PhD program. Faculty of a student that know other faculty. Students finding their POI at a conference and getting face-time...they are playing the game. In IO we learn about how the most random factors like name and handshake can affect your likelihood to receive a job offer, especially when the process is unstructured. The application process is very unstructured: some professors hate the GRE, some love applied experience, some publications, sometimes it's just random in terms of who you apply to. It's hard not to take it personal. Graduate applicants are conscientious; you can tell by the path they've chosen.  However, I've never met someone intrinsically motivated that didn't get in. Keep hope. Learn. Find out what the accepted candidates "had" that you didn't. Objectively you may have been much higher on the list, but the list isn't objective; otherwise, a computer would select who gets in. 
 
 
In reality: I cry and listen to Katy Perry's "The One That Got Away"

Best and Craziest: Find a 9-to-5 job. Spend my nights crying myself to sleep, but capture my tears. I'll save my tears until I can fill a bath tub. Proceed to bath in my tears, but record it and post it on social media. The post will go viral, igniting my YouTube career. In my videos, I'll call out all those who've rejected me in the past; though I will still cry myself to sleep at night. 

The one thing I've derived from being in psychology is that you learn "it depends" over and over again. People aren't like gravity or sound, thus of course people will have different reasons. Some applicants want an adviser that fits them perfectly; some what to escape the clutches of their parents; others may not want to graduate knee-deep in debt. However, the intention of the post is not to standardize decisions, it's to provide insight to those that are struggling. From my perspective it's less about what decision is the correct decision and more about what decision you believe in- sometimes all that takes is someone telling you that you're making the right decision. In 6 months time a lot of you will be perfectly fine with your choice. I've had a few interviews where fellow applicants were transferring from other PhD programs, but this was due to very random-effects (e.g., adviser moving away or they wanted to change fields); they still created the opportunity to decide again. 
 
Too long;didn't read: For a small fee, I'm willing to pick a program for you. You will like it. You have no right to question my methods.

The one thing I've derived from being in psychology is that you learn "it depends" over and over again. People aren't like gravity or sound, thus of course people will have different reasons. Some applicants want an adviser that fits them perfectly; some what to escape the clutches of their parents; others may not want to graduate knee-deep in debt. However, the intention of the post is not to standardize decisions, it's to provide insight to those that are struggling. From my perspective it's less about what decision is the correct decision and more about what decision you believe in- sometimes all that takes is someone telling you that you're making the right decision. In 6 months time a lot of you will be perfectly fine with your choice. I've had a few interviews where fellow applicants were transferring from other PhD programs, but this was due to very random-effects (e.g., adviser moving away or they wanted to change fields); they still created the opportunity to decide again. 
 
Too long;didn't read: For a small fee, I'm willing to pick a program for you. You will like it. You have no right to question my methods.

Don't panic! (easier said than done). We are still in "peak-season" for interviews, and it will continue until roughly the 3rd week in February. 

Be careful with advice like this, especially for I-O programs. The top programs differ on this not only between-schools, but between faculty at the department-level as well. Some schools do not follow a mentorship model where you have a primary advisor (e.g. Michigan State - you're expected to work with multiple faculty), and even at the schools that do have primary advisors, the faculty do not agree with each other on importance of fit. They are also not oblivious to the fact that your interests will likely change throughout your schooling (especially when you haven't taken the coursework yet). Be as honest as you can if you get an interview. There are no absolutes when it comes to the application process for I-O programs. The fit is perhaps more important for you as the student if you are dead-set in what you want to do, because you want a professor who can train you in what you want to do as well as possible.

I'm actually an applicant from last year. I wanted to drop-in and give everyone a frame-of-reference. First, good luck to everyone! This was one of the most humbling experiences of my life- but it will be worth it.
A note about my application: I had some pretty good credentials, however, research experience is critical (arguably the most important). I didn't have that at the time of my application. Here are my final application results:

School Program Title Interview Decision George Mason University PhD of Psychology: Industrial/Organizationa Concentration Yes Accepted - Attending George Washington University PhD of Industrial/Organizational Psychology Yes Accepted James Madison University PhD of Assessment and Measurement Yes Accepted NC State PhD of Industrial/Organizational Psychology No Rejected Old Dominion University PhD of Industrial/Organizational Psychology Yes Withdrew Application Penn State PhD of Industrial/Organizational Psychology No Rejected UNC Charlotte PhD of Organizational Science Yes Accepted UNC Greensboro PhD of Educational Research, Measurement, and Evaluation (ERM) Yes Accepted University of Maryland PhD of Social, Decision and Organizational Science (SDOS) Yes Waitlisted - Rejected University of Maryland PhD of Measurement, Statistics and Evaluation (EDMS) Yes Accepted  
Here is a summary of my credentials at time of application (last year):
Research Interests: Item Response Theory, Statistical Modeling, Job Analysis, Multidimensional Constructs, Assessment and Measurement Bias.
Degrees: BA in Psychology, MS in I/O Psychology
Test Scores and GPA:
GRE
Q: 160 (72nd)
V: 162 (91st)
AWA: 4.0 (60th)
GPA
Undergrad GPA: 3.97
Undergrad Major GPA: 4.0
Grad GPA: 4.0
Research Experience: 
2 poster presentations
3 Professional Board Presentations
Research Methods & Statistics TA 1 year
100+ hours applied research (MS was heavily applied)
No thesis
No peer-reviewed publications
Professional Experience:
2+ years Psychometric Data Analyst (current)
1 year Teaching Fellow
1 year Teaching Assistant 
1.5 years Research Developer
Summer HR internship
Worried About: Lack of thesis and publications, mediocre GRE Quant, all of you awesome people
_________________________________________________________________________________________________
Here is also a thread that was created a while back to (hopefully) make your lives a lot easier.
Data for 2019 Applicants
If anyone has any questions or thoughts about their application (or mine)- please reach out to me:
My Email
 
All the best,
 

Yes, I wouldn't make any inferences based in the GPA and GRE scores. If you notice the black bars (standard errors) overlap on all of them. Good catch. What should make everyone feel better is the fact that perfect scores aren't as common in this data. 
 

Here you all are:
Data on decisions
This was a project I did last year. It doesn't include results as of this year but the sample is quite high (~35000). Keep in mind it's based on the results survey, so there may be over or under reporting (i.e., people may be more likely to report interviews than waitlists, or acceptances more than rejections) and some other biases.
 

Yes, I wouldn't make any inferences based in the GPA and GRE scores. If you notice the black bars (standard errors) overlap on all of them. Good catch. What should make everyone feel better is the fact that perfect scores aren't as common in this data. 
 

Yes, I wouldn't make any inferences based in the GPA and GRE scores. If you notice the black bars (standard errors) overlap on all of them. Good catch. What should make everyone feel better is the fact that perfect scores aren't as common in this data. 
 

Here you all are:
Data on decisions
This was a project I did last year. It doesn't include results as of this year but the sample is quite high (~35000). Keep in mind it's based on the results survey, so there may be over or under reporting (i.e., people may be more likely to report interviews than waitlists, or acceptances more than rejections) and some other biases.
 

Here you all are:
Data on decisions
This was a project I did last year. It doesn't include results as of this year but the sample is quite high (~35000). Keep in mind it's based on the results survey, so there may be over or under reporting (i.e., people may be more likely to report interviews than waitlists, or acceptances more than rejections) and some other biases.
 

Here you all are:
Data on decisions
This was a project I did last year. It doesn't include results as of this year but the sample is quite high (~35000). Keep in mind it's based on the results survey, so there may be over or under reporting (i.e., people may be more likely to report interviews than waitlists, or acceptances more than rejections) and some other biases.
 

Here you all are:
Data on decisions
This was a project I did last year. It doesn't include results as of this year but the sample is quite high (~35000). Keep in mind it's based on the results survey, so there may be over or under reporting (i.e., people may be more likely to report interviews than waitlists, or acceptances more than rejections) and some other biases.
 

I'm actually an applicant from last year. I wanted to drop-in and give everyone a frame-of-reference. First, good luck to everyone! This was one of the most humbling experiences of my life- but it will be worth it.
A note about my application: I had some pretty good credentials, however, research experience is critical (arguably the most important). I didn't have that at the time of my application. Here are my final application results:

School Program Title Interview Decision George Mason University PhD of Psychology: Industrial/Organizationa Concentration Yes Accepted - Attending George Washington University PhD of Industrial/Organizational Psychology Yes Accepted James Madison University PhD of Assessment and Measurement Yes Accepted NC State PhD of Industrial/Organizational Psychology No Rejected Old Dominion University PhD of Industrial/Organizational Psychology Yes Withdrew Application Penn State PhD of Industrial/Organizational Psychology No Rejected UNC Charlotte PhD of Organizational Science Yes Accepted UNC Greensboro PhD of Educational Research, Measurement, and Evaluation (ERM) Yes Accepted University of Maryland PhD of Social, Decision and Organizational Science (SDOS) Yes Waitlisted - Rejected University of Maryland PhD of Measurement, Statistics and Evaluation (EDMS) Yes Accepted  
Here is a summary of my credentials at time of application (last year):
Research Interests: Item Response Theory, Statistical Modeling, Job Analysis, Multidimensional Constructs, Assessment and Measurement Bias.
Degrees: BA in Psychology, MS in I/O Psychology
Test Scores and GPA:
GRE
Q: 160 (72nd)
V: 162 (91st)
AWA: 4.0 (60th)
GPA
Undergrad GPA: 3.97
Undergrad Major GPA: 4.0
Grad GPA: 4.0
Research Experience: 
2 poster presentations
3 Professional Board Presentations
Research Methods & Statistics TA 1 year
100+ hours applied research (MS was heavily applied)
No thesis
No peer-reviewed publications
Professional Experience:
2+ years Psychometric Data Analyst (current)
1 year Teaching Fellow
1 year Teaching Assistant 
1.5 years Research Developer
Summer HR internship
Worried About: Lack of thesis and publications, mediocre GRE Quant, all of you awesome people
_________________________________________________________________________________________________
Here is also a thread that was created a while back to (hopefully) make your lives a lot easier.
Data for 2019 Applicants
If anyone has any questions or thoughts about their application (or mine)- please reach out to me:
My Email
 
All the best,
 

Hello everyone,
I've seen quite a bit of chatter around the timing of results, and the answers are obscure. I wanted to provide my services, and give you all some extra data. The beauty of grad cafe is that it is one of the most (if not the most) centralized data source for graduate students. Some data examples: What schools are most popular, what degrees, applicant metrics, dates of results, etc. Yet, I've yet to find someone that uses this information to help those applying.
 
Until now...
 
I used R (for those unfamiliar) to scrape the grad cafe results data related to psychology. I returned about 35000 records. There were a lot of un-tidy text strings (e.g., PhD and Ph.D.), especially in relation to program-title and institution; however, that is a project for another day. Data regarding dates and decisions did seem clean enough for me to analyze it and turn it into something nice for you all.
 
So what is it....?
Here is a PDF based on the results of all Psychology students (over 35000) since the origin of grad cafe. The first 3 tables show the 10 most common dates (by count) for getting an interview, getting accepted, and getting rejected ? .  I would do relative frequency and should've...maybe tomorrow.
Then a longitudinal line graph (which shows these decisions throughout the year)
Finally, one that focuses more on the "critical-period" when most decisions are made.
 
Conclusion
This was a piecemeal job that I should be done in R Markdown. I'll link my code at the end. Similar methods could be used to look at the "most popular" programs, probability of acceptance by degree type or program type, average GRE score for accepted candidates, and the list goes on. If anyone wants a csv of the dataset I used, please feel free to message me. I also welcome critiques and suggestions.  I wish you all the best.
 
R code here

All,

It's that time of year again. Apparently time flies when you're filled with anxiety. I was an applicant in 2018, and I had quite a fruitful experience during the application process (a lot of it due to this website). However, that is not why I'm here. I'm here to provide you with information that, hopefully, will make your journey a little easier than mine. Here are some posts that may help:

The things I wish I knew before applying
Data on application trends
Thoughts about interviews
What do I look for in a program?
 
Please feel free to reach out. A vast majority of you are clinical students, whereas I'm in Industrial/Organizational but I'm more than willing to give a general impression of the process.

All the best,
-Left Skew
 

Hi Spyester,
I've been working in the I/O field for about 3 years and will be returning to academia to finish my doctorate (I have my M.S.). 
If I had to give you a general taxonomy of where I/Os end up it tends to be an intersection between people and work. Specifically:
Internal consulting- I would say this is the most common area, not positive though. Many HR departments will hire IOs the develop and improve processes related to: hiring, benefits, performance management, compensation, training, hr analytics, etc.
External consulting- your tasks are similar to the ones above, however, you work for a consultation firm that advises public agencies and large private organizations.
Academia- pretty self explanatory, you should have your PhD
Lesser know areas- Psychometrics, data science, and testing in general (I work in this realm)
 
Message me if you have anymore questions.
Best
 
 

I'm still feeling the pain of rejection of this years application cycle but I will be reapplying for Fall 2019. I'm graduating next month with my MS in clinical psych with a 4.0 (unless I have an epic stumble in the next few weeks). I'm a full time research assistant for a prestigious institution since 2015 for psychiatry, we focus on psychosocial rehabilitation, smoking cessation, and clinical trials for cannabis use disorder for people with serious mental illness. As of right now I have one publication and two poster presentations. I just submitted a manuscript and I am working on another paper and an abstract for a conference. 
My interest is in behavioral neuroscience but I am worried that my lack of hard science background was a detriment this time around. I majored in psychology and in neuroscience in undergrad and I took pre-med courses. However, my grades are all over the place. I would get B's and A's in hard science classes but then not did well in easier classes. This was mostly due to personal issues. My GRE scores are also abysmal. My boss and coworkers keep telling me to take a prep course and retake them. I know that I should but I just don't know if I can afford it.
This past cycle I applied to 13 schools and only had one interview. This time around I will probably stay around the same number but I honestly have no idea where to apply. I want to reapply to some of the same schools but I don't know if that's a bad idea or not. Thoughts?
Good luck everyone! I can also help answer questions since this isn't my first rodeo.   

All,

It's that time of year again. Apparently time flies when you're filled with anxiety. I was an applicant in 2018, and I had quite a fruitful experience during the application process (a lot of it due to this website). However, that is not why I'm here. I'm here to provide you with information that, hopefully, will make your journey a little easier than mine. Here are some posts that may help:

The things I wish I knew before applying
Data on application trends
Thoughts about interviews
What do I look for in a program?
 
Please feel free to reach out. A vast majority of you are clinical students, whereas I'm in Industrial/Organizational but I'm more than willing to give a general impression of the process.

All the best,
-Left Skew
 

Hello everyone,
I've seen quite a bit of chatter around the timing of results, and the answers are obscure. I wanted to provide my services, and give you all some extra data. The beauty of grad cafe is that it is one of the most (if not the most) centralized data source for graduate students. Some data examples: What schools are most popular, what degrees, applicant metrics, dates of results, etc. Yet, I've yet to find someone that uses this information to help those applying.
 
Until now...
 
I used R (for those unfamiliar) to scrape the grad cafe results data related to psychology. I returned about 35000 records. There were a lot of un-tidy text strings (e.g., PhD and Ph.D.), especially in relation to program-title and institution; however, that is a project for another day. Data regarding dates and decisions did seem clean enough for me to analyze it and turn it into something nice for you all.
 
So what is it....?
Here is a PDF based on the results of all Psychology students (over 35000) since the origin of grad cafe. The first 3 tables show the 10 most common dates (by count) for getting an interview, getting accepted, and getting rejected ? .  I would do relative frequency and should've...maybe tomorrow.
Then a longitudinal line graph (which shows these decisions throughout the year)
Finally, one that focuses more on the "critical-period" when most decisions are made.
 
Conclusion
This was a piecemeal job that I should be done in R Markdown. I'll link my code at the end. Similar methods could be used to look at the "most popular" programs, probability of acceptance by degree type or program type, average GRE score for accepted candidates, and the list goes on. If anyone wants a csv of the dataset I used, please feel free to message me. I also welcome critiques and suggestions.  I wish you all the best.
 
R code here

Since it seems this thread has died down I just want to thank everyone for all the help/support/discussions! Best of luck on this long grind.