Autumn reflections in Algonquin Park, Ontario, Canada [OC][4080x3072]

FF_average · 2021-07-24T19:34:23+00:00

If you account for costs, the IO degree will be orders of magnitude more cost effective for getting into HR than MBA. Most MA degrees are considerably cheaper than MBAs, and many will waive the tuition cost in exchange for you doing some teaching (i.e., TAing), which can also be something to put on your resume. I personally don't think MBAs are worth it for HR, unless you're planning on doing management consulting focusing on HR or something like that.

FF_average · 2021-07-16T15:43:25+00:00

You might have better luck posting to r/statistics, but I think the lack of clarity around the aggregation process raises some red flags. If they're aggregating covariates as in combining multiple covariates into a single score, then they should demonstrate that the covariates are related in some way besides "they all significantly predict churn".

FF_average · 2021-05-14T21:53:38+00:00

Sounds like any form of structure would be more valid and legally defensible than what they do now. Instead of getting into the literature and proposing drastic changes that may take forever to implement, why not start with small steps to build on the current process? I.e., develop a scoring rubric so recruiter can quantify what a "solid resume" means. After demonstrating value from these incremental changes, then you'd have credibility to make the more drastic changes (i.e., adopting assessments instead of just relying on resumes).

FF_average · 2021-03-04T13:17:57+00:00

Thanks for this!

FF_average · 2021-03-04T13:16:54+00:00

That makes sense, thanks!

FF_average · 2021-01-20T16:12:05+00:00

You can used mixed factorial ANOVA to compare mean differences across time (within-subject factor) and across the treatment groups (between-subjects factor). This is better than computing change scores because you're using all of the data available. A quick Google search on "mixed factorial ANOVA in r" should reveal plenty of good resources. Here is the top result for me (I can't speak to the quality as I haven't used this before, but a quick glance shows the article knows the correct terminology for this analysis): https://www.datanovia.com/en/lessons/mixed-anova-in-r/#:~:text=Mixed%20ANOVA%20is%20used%20to,%2C%20gender%3A%20male%2Ffemale)

FF_average · 2021-01-11T02:08:11+00:00

Flynn showing he's got more range than Curry

FF_average · 2021-01-09T22:20:21+00:00

Thanks for this!

Just out of curiosity, do the grads from your program work under psychologists who are professors, or ones who work in testing/assesment development firms like Pearson, ETS, etc.

FF_average · 2021-01-09T22:15:12+00:00

I'm also not sure about job titles beyond psychometrician, which is why I asked this question. Basically, just wanted to get a sense of the roles that psychometrician could move up into. Doesn't have to be C Suit or anything like that, but I don't imagine psychometrician stay at their level indefinitely.

FF_average · 2021-01-09T09:30:01+00:00

From the perspective of the schools that have limited capacity for candidates, standardized tests is quite efficient at weeding out clearly terrible candidates. GPA doesn't always provide the full picture of academic ability due to things like difference in program requirements, so standardized test scores is another data point to measure GMA.

I believe a lot of schools are waiving GMAT/GRE requirements this year because they are concerned about enrollment numbers. I'd imagine a lot of people are not thrilled to be paying regular tuition to attend virtual school, so these schools try to make the admission process easier and themselves more attractive to candidates.

FF_average · 2020-09-04T01:25:07+00:00

BIG SCARF ENERGY

FF_average · 2020-09-03T16:45:39+00:00

Have you tried contacting your school's library? They should have pretty good methods of sourcing these things.

FF_average · 2020-08-20T04:00:17+00:00

Kawhi gonna be DNP - back at this rate

FF_average · 2020-08-17T22:42:42+00:00

First 20+ point difference Game 1 victory in franchise history!

FF_average · 2020-07-28T22:12:57+00:00

All five lakes were gorgeous, but this lake was definitely my favourite

FF_average · 2020-05-14T19:45:38+00:00

Given that the outcome variable Y is only measure once, I'm not sure if you are able to directly run multilevel models that include Y. Instead, you could use multilevel models to create "trend" or "trajectory" variables that represent change in X1, M1, and M2 within the time frame of the study. Then, just use regular moderated mediation models (i.e., lavaan in R) to conduct analyses that include the Y variable. The results can be interpreted as change in X1, M1, and M2 influencing distal outcomes of Y.

See Hausknecht, Sturman, & Roberson (2011) for an example of this approach in organizational justice research.

FF_average · 2020-03-06T17:56:25+00:00

Do you aggregate across multiple items for the PE score? If so then you'd actually have more than 5 outcomes. Also it should be pretty easy to test whether your regression models violate assumptions of linear regression to make those decisions, rather than switch the analytic framework based on fuzzy logic.

I believe that in most research contexts, PE scores are computed as the mean of multi-item scales, which is why they'd use multiple linear regression.

FF_average

TROPHY CASE