What are /r/IOPsychology's favorite Products & Services?

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Did you take many statistics classes during undergrad? If not I’d start there. But if you feel like you have a good grasp of basic statistics, I suggest learning Rstudio, Python, and SQL.
* This book is excellent for learning R.

• This book is a really good starting point for Python.

The final paragraph of this paper will be of interest:

To summarize, we are left with serious doubts concerning the construct validity of at least the assessment of Emotion Perception with the MSCEIT. Since validation is a cumulative enterprise, we cannot completely discount this EI measure at this stage. Further research will have to replicate the results presented here and extend the approach to other subscales of the MSCEIT. Nevertheless, at this stage we can not suggest that the MSCEIT has stood a test of an

important aspect of the validation process.

https://www.semanticscholar.org/paper/Exploring-the-validity-of-the-Mayer-Salovey-Caruso-Roberts-Schulze/2d7efad38c79acdd0f1e680640c1bb03e6459633?p2df

I'd also suggest joining on LinkedIn Minnesota Professionals for Psychology Applied to Work MPPAW as I would think there are multiple there who would be a fit.

Pretty cool. Its creator explains his methodology and assumptions in this LinkedIn group: https://www.linkedin.com/groupItem?view=&gid=72806&type=member&item=5941227825175502856&trk=groups_most_popular-0-b-ttl&goback=%2Egmp_72806

Nice work! Do you know Lars Schmidt? He's running HR Open Source. Here's a sample of what he's put together. https://coda.io/@lars-schmidt/redefining-hr-open-source-learning-lab

You might send your site his way to be included there, too. Congrats and well done!

Our lab just started using slack and asana for communication and project management respectively. I have already noticed increased productivity in the couple weeks we have been using them. Source: neuroscience grad student.

"So Good They Can't Ignore You" by Cal Newpot

"Mindset: The New Psychology of Success" by Carol Dweck

"A Whole New Mind" by Daniel Pink

"Quiet: The Power of Introverts" by Susan Cain

Incognito: The Secret Lives of the Brain" by David Eagleman

"Thinking Fast and Slow" by Daniel Kahneman

"The Logic of Collective Action" by Mancur Olsen

"Nudge" by Richard Thaler

"Judgment in Managerial Decision Making" by Max Bazerman

"Blind Spots" by Bazerman & Tenbrunsel

"Influence: The Psychology of Persuasion" by Robert Cialdini

"The Invisible Gorilla" by Christopher Chabris

Lin, Ma, & Johnson (2016). https://www.researchgate.net/profile/Russell_Johnson5/publication/291333973_When_Ethical_Leader_Behavior_Breaks_Bad_How_Ethical_Leader_Behavior_Can_Turn_Abusive_via_Ego_Depletion_and_Moral_Licensing/links/56bded5408ae2f498ef61330.pdf

Not an IO PhD, but I use my Surface Laptop for most school related tasks. Reading (textbooks/papers) typically occurs on an iPad. When I am home, I use a desktop I built with two 1440/144hz monitors.

None of this really matters, though. All the heavy lifting is done through one of our servers, so I could run data on almost anything.

>In all the talk about the mismatch between the projected number of STEM jobs (1.2 million new ones in the next six years) and the U.S.-based talent to fill those positions, we’re losing sight of another big skills gap that’s right under our fingers every day.

>Ninety percent of all jobs in the next year will require information and communication technology skills, according to research by Capgemini.

There's a big discrepancy between surveys of companies on the "skills gap" and what the empirical data actually show: https://www.linkedin.com/pulse/article/20140718161442-229136910-the-biggest-lie-in-hiring-the-skills-shortage

Full disclosure: I wrote the article linked above.

>one in ten young people are rejected from a job because of their social presence on the web.

I see bad hiring practices :(

Sure thing! It was this handbook volume by Schmitt & Highhouse.

Huh, weird. We had a whole course on job analysis & this was our book... https://www.amazon.com/Job-Work-Analysis-Applications-Management/dp/1544329520/ref=asc_df_1544329520/?tag=hyprod-20&linkCode=df0&hvadid=266029226073&hvpos=&hvnetw=g&hvrand=17453681733903990139&hvpone=&hvptwo=&hvqmt=...

My go to: https://www.amazon.com/Transforming-Performance-Management-Applied-Psychology/dp/1138051969

There's definitely no one best method, I've likened searching for the 'best performance management" process to trying to find the "best weight loss method." The basics of PM will always include goal-setting, measurement, feedback, and evaluation but how often, to what extent, and at what level or formality are moderated by environment and culture of the org.

No applied experience in IO/HR, sadly!

But, a useful popular press introduction to the topic: https://www.amazon.com/Neurotribes-Legacy-Autism-Future-Neurodiversity/dp/0399185615

I am not a fan of Musk.

I've been reading up on expertise development and elite performance for some time. It's fairly traditional learning theory stuff and just crossed into decision making and complexity. It's like going to the center of the Earth and the gravity inverts. Things get really counterintuitive. Eduardo Salas does a lot of work here.

I just really started on this in the last week, but for cognitive flexibility training, it's best not to teach individual knowledge bits as that can impede later learning. SO learning from the complete bottom-up often leads to rigidity which is counter to a lot of learning theory.

Coincidentally, I've learned a ton about the Top Gun program and how successful it was. The navy was able to turn their pilots into being between 3-6 times more effective than the airforce in a relatively short time as far as kill rate. The navy beating the airforce by that much is incredibly impressive (at least to me).

https://www.amazon.com/Accelerated-Expertise-Training-Proficiency-Applications-ebook/dp/B00EKN8ZGE

Also, I'm working on validating common commercially available assessments for assessing ability to work cross-culturally. Not like real validation, but just reviewing instruments for quality and if there is any evidence of real validity and usefulness.

Pointing you in the direction of Gordon Curphy and Diane Nielson. https://www.amazon.com/Ignition-Guide-Building-High-Performing-Teams/dp/0578603160/ref=sr_1_7?qid=1653479498&refinements=p_27%3AGordon+Curphy&s=books&sr=1-7

Just picked up Inclusalytics. It’s written by an I/O PhD consulting in the DEI space. A solid primer on thoughts regarding DEI, how to measure DEI successes, and a demo of some common I/O tools like surveys, dashboards, etc., and research methods-lite for topics like reliability, validity, etc.

If you’re at the PhD level or have had a few years of applied I/O-relates work, the book is more of a fundamentals brush up. It definitely seems geared at HR or leaders who want to pursue DEI initiatives but perhaps may lack the stats/methods training. I think it’s also helpful for a masters-level graduate who may not have as much training in thinking about research design or a recent PhD grad with limited work experience.

In the latter case, I would focus more on the business concerns portions of the book such as leveraging buy-in and delivering benchmarks that non-data experts can make sense of (aka don’t try to do slides on regression R-squares and statistical significance for an HR BP with little stats training or you’re gonna have a bad time).

>Applied Industrial/Organizational Psychology by Mike Aamodt

Michael Aamodt, was struggling to find it under Mike

https://www.amazon.co.uk/Industrial-Organizational-Psychology-Applied-Approach/dp/1305118421

Guion & Highhouse, 2006 was one of the most straight-forward, and complete books concerning employee selection I've ever found. It's succinct and provides many practical examples of most of the basic considerations required in employee selection. There's a newer edition that I image is equally good.

Here is one of my favorite recent papers - just a beautifully designed study on an important and - given the election - very relevant topic. https://www.researchgate.net/publication/264418541_Leader_corruption_depends_on_power_and_testosterone

Lots on this already in the self-regulation literature.

The Cartoon Guide to Statistics is a little cheesy, but might be helpful as you think of ways to translate technical information to non-technical audiences.

Haven't done this. Once I bookmarked this resource as it looked like a similar project *might* come my way: https://www.amazon.com/Strategic-Workforce-Planning-Guidance-Back-Up/dp/1478317175

Ah, well OP gave some useful references on learning about job analysis too, but they deleted their comment. I think this is the book most would recommend for practitioners needing to learn more about job analysis: https://www.amazon.com/Job-Work-Analysis-Applications-Management/dp/1412937469

The Psychology of Managerial Incompetency: A sceptic’s Dictionary of Modern Organizational Issues

Every time I see something like this, I'm reminded of that Twitter thread on the validity of the GRE. She also speaks to this on the 2 Psychologists 4 Beers podcast, which was excellent.

My main agreement is that even with its known flaws, standardized testing is a far more fair form of evaluation compared to interviews, personal statements, or letters of recommendation. It's bleak thinking of all the universities abandoning these tests and not realizing that they're just reinforcing inequality, since it's much harder to fake on a standardized test than it is to have prestigious connections, excellent extracurriculars, lab experience, etc.

Which resources are you using to learn machine learning? Are you teaching yourself to program?

I really like the edX MIT course on stats and R: https://www.edx.org/course/mitx/mitx-15-071x-analytics-edge-1416#.U6Q0c41dVH8

And I'm sure you've heard of Coursera's Data Science specialization: https://www.coursera.org/specialization/jhudatascience/1

I just read this GitHub playbook on formalized informal interaction: https://about.gitlab.com/company/culture/all-remote/informal-communication/

A lot of good ideas! Basically, you have to plan and program informal socialization to occur online to replace/supplement spontaneous, in-person interactions that happen.

I think dark triad traits just naturally weaken over the lifespan. For example, O'Boyle et al. 2014 demonstrated that agreeableness explains a large portion of the variability in the dark triad, especially psychopathy and Mach, and agreeableness tends to increase as we get older (e.g., McCrae et al., 1999). However, I think you're also right that senior leadership roles disadvantage people with high dark triad traits, who generally perform best in short, unstructured interactions with high latitude for improvisation and low need for trust.

I would personally jot down the questions I am asked to investigate, and also the end goal. Ultimately what is it that you want to achieve for the end user. I would then do some background research on some Excel dashboards. I say excel because it’s free and almost all know it and can use it. If you know other platforms then do that.

Once you have some ideas of how other have built dashboards related to this topic, you should feel more comfortable building this ground scratch in Excel. Also, be mindful of the type of visual you are building for a specific analysis. For example, if you want to compare performance between groups (programs), using a bar chart could be good as you can compare categories. If you are trying to show trends over time, then a line chart may be more appropriate. These are some nuances when choosing the right chart type.

https://www.tableau.com/learn/whitepapers/which-chart-or-graph-is-right-for-you

Students can also get a full copy using the link below. You just enter your school information and download a copy. If they cannot verify your enrollment, a simple email will resolve it. You can renew the license every year you remain a student.

​

https://www.tableau.com/academic/students

Anyone seen this recent release: Science of Dream Teams by Mike Zani the CEO of the predictive index. I picked it up off the 'new' shelf at my library. I'm fairly certain it's going to be a sell-piece on the PI -but always curious what gets published in this space. If nothing else, there's a cool appendix in the background that gives a quick and dirty around commercial grade psychometrics and what the pros and cons are. These leader-facing books are helpful for me in learning language that resonate with execs that's convincing, relevant and persuasive for getting across my views on what will work and what's evidence based.

For anyone who is interested in reading more, Loren Baritz's The Servants of Power: A History Of The Use Of Social Science In American Industry is a good read.

Of course, I was in grad school when I read it and really became slightly disillusioned when the default answer to why we should do things kept being "to show ROI" or how journal articles had a specific mention of the research being beneficial due to the potential gains in productivity (and therefore $$$) for organizations to adopt.

For ML I would recommend practical statistics for data scientists as a starting point and just generally good to have in ur toolbox. It covers everything from basic stats to supervised and unsupervised methods and implementation in both R and Python.

For NLP personally I’ve used a mix of online resources to fit my use cases. I lean on python more than R for NLP though but if u can learn R u can learn python implementations (Jupyter notebooks are the same as R markdown). NLTK is one library you can look at for sentiment analysis and for things like topic modeling you can look into LDA (latent dirichlet allocation - not linear discriminant analysis). Word clouds are a pretty simple implementation as well. There are plenty of tutorials for all of these you can find online.

Also, from experience (and one reason I recommend that book) many ML courses and books get into ML topics that wouldn’t be relevant to IO work (e.g., image classification, computer vision) so make sure you review the material to be sure it’s relevant. It’s easy to go down rabbit holes of ML knowledge you won’t really need (at least at this level).

Good luck!

Do you have this? It's really inexpensive in it's ebook form.

Cambridge Handbook of Cognitive Science

>now added to my already too long to-read list.

I hear that.

​

I think I've seen both of those other books. I think the Oxford handbook is a lot more philisophical. I've been interleaving the expertise stuff with this: Routledge International Handbook of Ignorance Studies It's the anti-expertise book, sort of. It addresses when experts ignore info they don't really need which is one of the most general expert skills.

These books are becoming pretty inexpensive in ebook formats. I cot the new intercultural training handbook for $36. Many are $50. They used to cost $200 or more. Also, a lot of older editions are free through Google Scholar.

I like this book quite a bit, and it broke it down into interesting subsections.

Van Tiem Fundamentals of Performance Technology https://www.amazon.com/dp/1890289175/ref=cm_sw_r_apan_glt_fabc_YS517RA9DSXRBVXPAK9M

It seems that your comment contains 1 or more links that are hard to tap for mobile users. I will extend those so they're easier for our sausage fingers to click!

Here is link number 1 - Previous text "T&D"

^Please ^PM ^/u/eganwall ^with ^issues ^or ^feedback! ^| ^Delete

Wow, this is a huge question, one about methodology and approach.

The short answer is, using a standard, agreed set of criteria to make the decisions is best.

What that standard agreed set of criteria is will depend on your organization, strategy, and the people involved. 2 five-figure companies are very small organizations, you may be able to assess whether to keep every person in the organization in a very short amount of time. This will be different set of criteria than 2 nine-figure companies, with more roles, but fewer layers assessed overall, but still, using a structured set of agreed criteria. The criteria, in either case, is determined by what KSAOs are needed to deliver against the organizational strategy, given the structure that has been put into place. You should use reliable and valid selection methods, and these will consist of standard selection methods such as interviews, performance reviews, leadership assessments. Fairness will be determined by a number of factors, and validity is part of that.

If you are looking for a primer on org design quick and dirty, I recommend this book, in particular, chapter 6 looks at people practices: https://www.amazon.com/Designing-Dynamic-Organizations-Hands-Leaders/dp/0814471196 Unfortunately, I don't have a good resource of hand for M&A activity.

While you wait on the podcast, have you looked at this book? I recommend it frequently to Master's students who are struggling to translate their recommendations into ROI.

Furr and Bacharach (2014) is usually my go-to. (https://www.amazon.com/Psychometrics-Introduction-R-Michael-Furr/dp/1452256802)

There are a lot of online resources too. When learning IRT, I've always found it the most helpful to look at how the specific analysis has been published. Here's a good article for that (https://doi.org/10.1177/0013164408323241). There's a ton of others out there but hope this is a good start.

I think you’re looking for the field of psychometrics.

Undergrad textbook: https://www.amazon.com/Foundations-Psychological-Testing-Practical-Approach/dp/B00BJZHSVE

Graduate textbook: https://www.amazon.com/Psychometrics-Introduction-R-Michael-Furr/dp/1452256802

"Job and Work Analysis: Methods, Research, and Applications for Human Resource Management" by Brannick, Levine, and Morgeson is a great handbook with an overview of most foundational I/O principles. It's a great resource for any I/O, though I will say it's focus skews more on the "I" side. Here's a link.

This is the book we used in a similar class in my grad program. It's not laid out quite as you described. The practical examples are helpful, and it talks about developing constructs in early chapters. (No mention of construct map though)

https://www.amazon.com/Measurement-Theory-Action-Studies-Exercises/dp/0415644798

I'm also reading this right now. The Elements of Journalism: What Newspeople Should Know and the Public Should Expect it's pretty interesting to read along with the attitude literature.

I'm going down a rabbit hole following the attitude research, journalism theory, and almost daily well-written articles in major magazines and newspapers about political belief, disinformation, misinformation, conspiracy theories, and whatever else is going on these days.

I don't think it was ever really considered particularly valid or reliable.

The Personality Brokers: The Strange History of Myers-Briggs and the Birth of Personality Testing

It's all based on Jungian theory and the intuitions of the women that developed it. If I remember correctly it was ETS that first commercialized it and the MBTI creators drove all the test designers crazy with their psuedoscience.

Can you use amazon rentals where you are? You can get it for $10, seems pretty reasonable. Amazon Link

Here is another citation I recommend for you https://www.amazon.com/Asshole-Rule-Civilized-Workplace-Surviving/dp/1600245854

Your professionalism and responses in this thread I hope you're not teaching or practicing IOP.

Not finished with it yet, but so far Judea Pearl’s the Book of Why is really good too. His research and philosophy is extremely unique IMO bec ause he is a computer scientist by training educated in Machine and deep learning, but a lot of his work has focused on understanding causality. The book discusses why causality is so important and the need for us to solve that problem before we can get computers to pass the Turing Test. IMO extremely relevant to I/Os attempting to blend theory with AI.

https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/046509760X

Understanding Psychology as a Science by Zoltan Dienes

https://www.amazon.com/Understanding-Psychology-Science-Introduction-Statistical/dp/023054231X/ref=sr_1_1?ie=UTF8&qid=1484625691&sr=8-1&keywords=understanding+psychology+as+a+science

I think Power's Book Behavior: The Control of Perception is a great introduction to the Control Theory of Motivation and goal-directed behavior.

My undergrad text was by Aamodt: http://www.amazon.com/Industrial-Organizational-Psychology-Applied-Approach/dp/1111839972 . It nicely covers the major areas in reasonable detail. I am starting an I/O Masters this year- I'll post again when I know what my texts are.

In Australia you need to have an undergrad Psych background and some command of social research and statistics. No business education is required but work experience is valued.

> Any recommendations?

We used this in my undergrad I/O class:

Levy (2009): http://www.amazon.com/Industrial-Organizational-Psychology-Paul-Levy/dp/1429223707

And this in my undergrad organizational behavior class:

Colquitt et al., (2009): http://www.amazon.com/Organizational-Behavior-Essentials-Performance-Commitment/dp/0078112559/ref=sr_1_3?s=books&ie=UTF8&qid=1454017426&sr=1-3&keywords=colquitt+organizational

> Also, would experience in a neuroscience lab doing EEG research bolster my application?

Yes.

> And what types of jobs do you get/places do you work?

Lots of different stuff. For example, I'll be starting a PhD program in the fall, but I'm doing data science stuff now until then and have interned for a NGO, financial firm, and consulting firm in the past. The Levy book has interviews with people about their jobs to give you a better sense of what they do.

This has certainly piqued my curiosity. But as I suspected, I am sitting here with my Psychological Testing and Assessment textbook and it devotes a large section to talking about the issues with intelligence and especially implementation of the tests.

This passage at the end, beginning the summary is basically what I am referring to. However, there are 20 pages detailing everything from construct validity to culture.

I'll close by quoting the first sentence to the final paragraph to the passage I posted above:

"Unfairly maligned by some and unduly worshipped by others, intelligence has endured - and will continue to endure - as a key construt in psychology and psychological assessment."

As I said in a previous post, it's simply not that simple.

Employee engagement would be another "positive" area to look into, as well as resiliency. The first part of this book also looks up the alley of the domain of interest here.

I second the other comments on a few big points.

Focus on GRE. This is really what faculty focus on when weeding out the first wave of applicants. Competitive scores matter and can compensate for other things.

Research methods, psych stats, experimental design and analysis, take any psych methods courses you can find.

No reason to be defensive about a sociology degree, you only have a page or two in your personal statement to sell yourself, so focus on why you want to be an I-O exclusively.

I have a couple friends with bachelors in English and engineering. Hell, I know a faculty member who was originally physics in undergrad and clinical in grad school. You are not pigeonholed in any way.

A few things I might add. First, while the job in HR is great, if you have the time and a university/practitioner in the area, grab some volunteer experience in a lab or I-O office if you can. Sometimes faculty like to see useful application of spare time.

Second, it's not uncommon to take a year off between undergrad and grad school to get more experience or to focus on the GRE.

Third, if your university doesn't offer a course in I-O, pick up a copy of Muchinsky's psychology applied to work (http://www.amazon.com/Psychology-Applied-Work-Paul-Muchinsky/dp/0578076926). Used copies on Amazon for $11. Commonly used in I-O undergrad courses, and is very accessible. Read it, skim it, whatever works with your schedule. If something really piques your interest, read the corresponding chapter Handbook of I-O Psychology. Definitely not as accessible, but it provides a great summary of topic areas. Most universities have digital access to the chapters.

Best of luck to you. See you at SIOP.