tag:blogger.com,1999:blog-8909074830238091680.comments2014-04-24T19:11:39.611+10:00Jeromy Anglim's Blog: Psychology and StatisticsJeromy Anglimnoreply@blogger.comBlogger764125tag:blogger.com,1999:blog-8909074830238091680.post-80327314929300406362014-04-15T18:28:19.303+10:002014-04-15T18:28:19.303+10:00Thanks for this article. I spent about an hour try...Thanks for this article. I spent about an hour trying to figure out scoreItems {psych} using >help(scoreItems) ... 10 minutes after reading this and I finished my script. Brilliant. Thanks again.<br /><br />@ste_nickstenick1989http://www.blogger.com/profile/04791920896372981288noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-33638238211471711552014-03-28T22:14:44.033+11:002014-03-28T22:14:44.033+11:00Ahh i see.
I meant the subject couldn't perf...Ahh i see. <br /><br />I meant the subject couldn't perform the test ( single leg balance). She couldn't even hold it for a second. The actual tests gets over this by using a scale which gives points from 1- 100. So for unattempted task you get 0 points. But i don't have their scores hence. <br /><br />And you should write an E book. I will buy it. Anoopbalhttp://www.blogger.com/profile/17871276618033328611noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-69427430088461570572014-03-28T12:37:42.187+11:002014-03-28T12:37:42.187+11:00the standard deviation of component variables is t...the standard deviation of component variables is the same with z-scores. Thus, composites of z-scores effectively weight components equally.<br /><br />I'm not sure what you mean by could not do a test. You could mean did not sit the test, which means you have missing data. Or you could mean failed the test, which presumably means you have an issue of how to score a test where people vary on both how well they did something and whether they could do it at all.<br /><br />With missing data, there are many approaches. One simple one, i just to take the mean score for the data you do have on the person as long as they still have a certain number of scores. This is equivalent to imputing the person mean to the missing data. That said, missing data analysis is a complex issue.<br /><br />If it's an issue of how to score a test where you have some that failed, then that is really going to require some domain specific knowledge. In general, if you want to put all these people on the one scale, then I think at the very least someone who can not do a test at all should generally get a score worse than those who could do it but did it poorly.Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-6344594076611047332014-03-28T12:30:29.131+11:002014-03-28T12:30:29.131+11:00Is it because the standard deviation is similar wi...Is it because the standard deviation is similar with z scores ? But when you combine scores by adding the standard deviations could be very different. <br /><br />Also what do you when someone couldn't do the test or scores a zero ( like balance). And this test is time based so if I give zero it means she did it very very good. What do you suggest in this case? Thank you so muchAnoopbalhttp://www.blogger.com/profile/17871276618033328611noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-89140458551859609252014-03-28T11:43:40.642+11:002014-03-28T11:43:40.642+11:00You are going to get a different variable when you...You are going to get a different variable when you take a composite. Often it will be a more reliable variable. <br /><br />It's certainly possible to get a significant composite and for all the components to be non-significant. <br />There are several explanations for this.<br />The general statistical answer is that if several of the composites are close to significant and in the same direction (e.g., p=.09, p=.1, p=.15) then the combined variable may be enough to be statistically significant at .05.<br /><br />Equally, you could get the opposite where one or more of the components is significant but the composite is not.<br /><br />It's interesting to ponder whether the underlying effect size would be larger for composites or components. In general the increased reliability associated with composites and their more general nature, may lead to generally larger effect sizes. But this is certainly not guaranteed. <br /><br />Another nice thing about the composite is that it provides an overall test. When you have many component variables, you have issues of multiple testing (i.e., with associated increased risks of Type I errors).<br />Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-62501164341915715362014-03-28T02:30:31.876+11:002014-03-28T02:30:31.876+11:00I know composites gives an overall assessment of m...I know composites gives an overall assessment of multiple tests. But is there any statistical benefits to using composites?<br /><br />I have noticed in my composite scores, the composite turned out to be significant, but the individual components are not. I used the z scores to calculate composites of 3 variables.<br /><br />Why is this? Thank you so muchAnoopbalhttp://www.blogger.com/profile/17871276618033328611noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-57102316649863974812014-03-27T17:24:59.071+11:002014-03-27T17:24:59.071+11:00Awesome article! If you haven't yet, you shoul...Awesome article! If you haven't yet, you should check out careerexchange.com.au , it's an Australian job board for allied health professionals, so it's a good place to look for jobs in psychology. It also has tips and tricks that are especially relevant to allied health professions. Psych Presshttp://www.blogger.com/profile/08795617839123104566noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-18443374036269236942014-03-26T13:04:51.282+11:002014-03-26T13:04:51.282+11:00I'm not really sure what you are talking about...I'm not really sure what you are talking about. I know when people get reaction time data with many observations per participant that they sometimes extract individual quantiles to reflect aspects of each individual's reaction time distribution. This gives you more than just the mean which is particularly useful where the data is non-normal or contains outliers or where you where the variance is relevant and differs between people.Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-83947755194889862302014-03-26T12:29:28.280+11:002014-03-26T12:29:28.280+11:00Just came across this post: Have you seen composit...Just came across this post: Have you seen composite scores based on quartiles? I have seen tests which cuts the scores into quartiles and give them points , like 12. What is the advantage of doing this way? Thank you for your postings!Anoopbalhttp://www.blogger.com/profile/17871276618033328611noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-70691670624582048672014-03-14T02:03:43.740+11:002014-03-14T02:03:43.740+11:00Stephan, thanks for clearing that up. I am left wi...Stephan, thanks for clearing that up. I am left with one last hurdle, the bibliography part. I have always used <br />\begin{thebibliography}{99}<br />\bibitem{xxx}<br />\emph{xxxx}<br />but now, it is saying control sequence not recognized. How do I change the bibliography to work with apacite?.Sydney Muzokahttp://www.blogger.com/profile/07889282574552809816noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-56719094529124293342014-03-10T10:47:30.928+11:002014-03-10T10:47:30.928+11:00There are several options; the simplest would be t...There are several options; the simplest would be to convert to a z-score using analyze - descriptives -descriptives save as standardised variable.Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-90642097251463220422014-03-10T04:54:25.264+11:002014-03-10T04:54:25.264+11:00Hello Jeromy! This post is a great resource and I&...Hello Jeromy! This post is a great resource and I've learned a lot from it. For creating some basic (i.e., equally weighted) composite variables it was perfect! Now I'm trying to take the OPQ32r and map it to a 6 factor model of personality. I have the sten scores for the 32 components of the OPQ. The publishers manual provides a mapping to the 6 factor model (i.e., the rotated component matrix). I am trying to create composite variables using the components that have weights above .3 (including negative weights; i.e., humility has a negative relationship with extraversion). Once I create the composite variables, however, the means and standard deviations are no longer meaningful. I've seen people mention that you should rescale your composite to make it meaningful/interpretable again, but the only example that I found was in R and I couldn't follow it at all. I'm using SPSS. Any tips or guidance would be much appreciated. Thanks! n.gintherhttp://www.blogger.com/profile/02613093288733640382noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-243181964110232612014-03-06T06:48:01.976+11:002014-03-06T06:48:01.976+11:00Hey Jeromy thank you so much for posting all the l...Hey Jeromy thank you so much for posting all the lectures and data. This has helped me better articulate the use of particular techniques in both SPSS and R! Keep up the good work.Simmyhttp://www.blogger.com/profile/04181813388093190303noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-5554635110301983202014-03-03T04:46:04.805+11:002014-03-03T04:46:04.805+11:00A nice tip is to Set Endnote to use page-range as ...A nice tip is to Set Endnote to use page-range as its identifier (rather than the random internal ID sequence it uses by default).<br /><br />References are then inserted like this {Anglin, 2013, 89-90}<br /><br />That makes them transportable and recoverable.<br /><br />I also set up a key-command in word/endnote for "insert selected reference", then once you have the ref in Endnote, it's trivial to replace it in the word document.<br /><br />I use ^⌥-1 as the key (and ^⌥-1 as the short cut for building the bibliography)<br />Timothy Bateshttp://www.blogger.com/profile/12707381996365946983noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-29701273416225609072014-02-24T02:50:27.306+11:002014-02-24T02:50:27.306+11:00Thanks for this post, made using apastyle much eas...Thanks for this post, made using apastyle much easier!<br />If you still maintain this, maybe add the following hint:<br /><br />\usepackage{apacite} has to stand AFTER \usepackage{hyperref} otherwise citations might not work (it's also written in the apacite manual, but damn I took time to find out what the problem was with my latex)<br /><br />This is a solution to problems like : ! Paragraph ended before \@cite was complete. Stephan Arndthttp://www.blogger.com/profile/02710635150056355329noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-52802878087513394652014-02-02T22:34:51.416+11:002014-02-02T22:34:51.416+11:00Hi Nick. Thanks for the comment. It's fun for ...Hi Nick. Thanks for the comment. It's fun for me to look back at a post I wrote four years ago. I find myself using Bayesian hierarchical models a lot these days, for among others things, the flexibility that they bring to modelling individual differences in change.Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-70011140729557487472014-02-02T21:17:01.960+11:002014-02-02T21:17:01.960+11:00I've been studying change in personality varia...I've been studying change in personality variables lately too, specifically well-being (guess I might as well plug my dissertation here too: http://www.escholarship.org/uc/item/3t34c68w). I've become somewhat concerned with the risk of combining measurement errors across longitudinal observations in ways that might increase kurtosis. To avoid the issue, I've been looking into latent change regression, and thought I'd mention it here. Check out McArdle (2009) if you haven't yet; I'm only about 1/3 through it and already learning a ton!<br /><br />McArdle, J. J. (2009). Latent variable modeling of differences and changes with longitudinal data. Annual Review of Psychology, 60, 577–605.Nick Staunerhttp://www.blogger.com/profile/13279286644389607457noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-12287078844779724312014-02-02T20:48:59.714+11:002014-02-02T20:48:59.714+11:00Hey Jeromy! I just read your article on the Big F...Hey Jeromy! I just read your article on the Big Five and subjective / psychological well-being...It's exciting! I have very similar data myself that I'm preparing for publication using SEM in R (based on my dissertation: http://www.escholarship.org/uc/item/3t34c68w). I think I'll have to cite you and your colleagues in the final version! Later, I'll be sure to see what I can replicate of your results. It should be very interesting to compare your Australian managers to my southern Californian undergraduates!<br /><br />As for the general topic of SEM in R, I've posted some tips recently over on Cross Validated about latent common factor modeling in R (http://stats.stackexchange.com/a/77314/32036) and SEM in general (http://stats.stackexchange.com/a/83545/32036). I've been studying these topics in depth lately, so I've touched briefly on a few advanced ideas and references about choice of estimator and how to relax model constraints when using the same data to both explore and confirm latent structure...but I've also laid out a sort of basic walkthrough for SEM in general (particularly for analysis of Likert scale ratings) that people who are very new to using SEM (like I was a few months ago) might find useful. I hope these are helpful, and would appreciate any feedback!Nick Staunerhttp://www.blogger.com/profile/13279286644389607457noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-69618070235580736022014-01-17T23:17:18.485+11:002014-01-17T23:17:18.485+11:00Great - thank you!Great - thank you!Dina Applebyhttp://www.blogger.com/profile/08995385018611166495noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-888618724567795212014-01-17T11:51:41.669+11:002014-01-17T11:51:41.669+11:00Percentage change of a change on an interval varia...Percentage change of a change on an interval variable sounds fine.<br /><br />I've often talked about this in the context of personality faking research.<br />For example, the presence of warning not to fake might reduce the change from an honest to applicant condition from d=.5 (without warning) to d = .3 (with warning) so the warning reduced faking by 40% (i.e., (.5 - .3) / .5). Even though the dependent variable is interval at best with no absolute zero, this still makes sense. <br /><br /><br /><br /><br />Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-24031204315576904692014-01-17T05:41:09.791+11:002014-01-17T05:41:09.791+11:00Okay, now I've gone beyond the stats question ...Okay, now I've gone beyond the stats question to more of a thought experiment. In fact, I'm playing devil's advocate by now arguing the OPPOSITE side of my prior argument, and suddenly I'm confused.<br /><br />I am in agreement that it doesn't make sense to talk about "25%" of a value that doesn't have an absolute zero. For example, using temperature (in degrees F or C) as our scale, we can't talk about 25% of 40 degrees (because what would be 25% of 0 degrees?) Similarly, we can't talk about a CHANGE of 25%: if it's 40F degrees on Tuesday, and 0F degrees on Saturday, has the temp dropped 100%? Obviously not, since if we used Celsius instead we would go from 4.4C to -17.8C, a drop of over 500%.<br /><br />BUT: Could we talk about a % change of a change? <br /><br />Here’s an example: Say you are concerned about the poor insulation in your attic. You complain to your spouse/roommate/landlord about this, but s/he ignores you. So you first take measurements to show how bad the problem is. Every day for two months in the summer, you measure the temperature in the attic at 8:00 a.m. (which is usually comfortable, close to the temp in the rest of the house), and then you measure it again at 5 p.m., when it is much hotter. After 60 days, you calculate that the mean daily temperature change is 24 degrees F (say, from 80F to 104F here in Philadelphia.) You present this info, and the response is, "Okay, but I can't put in enough insulation to keep the temperature constant all day - that would be way too expensive!" So you say, "I understand. But could you at least insulate it enough to cut that temperature increase in half?" Here, half of 24 degrees F is 12 degrees F; you are saying you could live with that level of average increase (e.g., from 80F to 92F.) Maybe the antique books you store in the attic won’t suffer as a result of that level of daily temperature fluctuation.<br /> <br />In Melbourne I presume you would present the same scenario as an intolerable mean daily increase of 13.3 degrees C, from 26.7 to 40C, which might be acceptable if it were cut in half: from a daily increase of 13.3 to a daily increase of just 6.65 degrees C. Thus, an average afternoon would top out at 26.7 + 6.65 = 33.35C = 92 F. In other words, the same PERCENT CHANGE OF THE MEAN CHANGE gives the same results no matter which scale you use, C or F. <br /><br />This “% change of a change” is really what the PI is asking me to use in doing the power calculations for the “Global-Cog” measurement. The population here is people with Alzheimer’s and other neurodegenerative diseases. There is no known cure for these conditions, which inevitably lead to declines in memory and other measures of cognition. <br /><br /> But: we want to do a study to see if our proposed intervention will reduce the RATE OF DECLINE (or the mean total decline over Y years) by, say, 25%. <br /><br />So now I’m thinking that this actually DOES make sense; that is, if the mean decline in our composite variable GLOBCOG is X points per year, saying we hope to change that to 0.75X is just as legitimate as saying that we want to change it to X-Z. <br />Or is it?!? <br /><br />Thanks!<br />Dina (now with a headache…..)<br /><br />Dina Applebyhttp://www.blogger.com/profile/08995385018611166495noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-48659562825542779072014-01-16T23:20:16.521+11:002014-01-16T23:20:16.521+11:00Thanks so much for your very prompt reply!
You ...Thanks so much for your very prompt reply! <br /><br />You wrote, "I think your issue is that you want your statements to have meaning." Yes, yes, yes!<br /><br />Alas, the same qualities that have always made me very successful as a student seem to cause me grief in the working world, even when that world is academia. :( Thanks for understanding!Dina Applebyhttp://www.blogger.com/profile/08995385018611166495noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-18691435795347296322014-01-16T18:40:46.394+11:002014-01-16T18:40:46.394+11:00In SPSS use "transform - compute" to cre...In SPSS use "transform - compute" to create a new variable. You can do basic arithmetic on existing variables in addition to apply a wide range of functions.Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-35274679393469838972014-01-16T18:36:50.427+11:002014-01-16T18:36:50.427+11:00Hi Jeromy,
Happy new year and me again! I tried s...Hi Jeromy,<br /><br />Happy new year and me again! I tried stats.stackexchange.com, however, the response (yours) was on R software, which I wouldn't know from a bar of soap. I am using SPSS and GraphPad Prism.<br /><br />Thanks for your help.<br />I have composite Z scores for a few cognitive tests. The Z scores are not normally distributed. If I log transform (log 10), the values less than 0 are not transformed. Funnily, the normality plot is nearly gaussian in appearance, however KS, D'Augostino and Shapiro-Wilks all show that the data is not normally distributed (p<0.02 to <0.0001). Hence, as a rule of thumb, I used Log transformation rather than SQRT or the other methods. What am I doing wrong? How best do I proceed? Your suggestion to add a constant so the minimum value is '1' makes perfect sense, but I am not sure how to do it in SPSS or GraphPad Prism.<br /><br />Please help and a million thanks in advance.<br />Regards, Vaidy Vaidy Swaminathanhttp://www.blogger.com/profile/08523458529737803536noreply@blogger.comtag:blogger.com,1999:blog-8909074830238091680.post-84370670058174435782014-01-16T11:45:31.909+11:002014-01-16T11:45:31.909+11:00I've just had a quick read. It sounds like you...I've just had a quick read. It sounds like you understand what's going on. As you note, percentage reduction does not make sense on a variable that lacks an absolute zero. Cognitive ability is typically conceptualised as a latent variable. It is often assumed to have a normal distribution. In this sense, you could see it as an interval variable. <br /><br />You can certainly model the effect of time on the composite z-score measure of cognitive ability. I think your issue is that you want your statements to have meaning. You may find it useful to convert the composite z-score into an actual z-score based on the standard deviation at time 1. Then, change over time will be on a meaningful z-score metric. Another alternative metric would be intelligence scores (i.e., mean = 100, sd=15), although there would be questions of what norm the value of 100 relates to.<br /><br />So avoid percentage change statements, and instead talk about change in standard deviation units. <br /><br />1. it is fine to compare change by groups: That would be some form of time by group interaction in ANOVA, random-effects modelling, etc.<br /><br />2. You can code time in a variety of ways. E.g., if you have observations for baseline plus five years, you could code it 0,1,2,3,4,5, or 0,.2, .4, .6, .8, 1. How you could time will influence the meaning of any coefficient. So in short it's fine to try to get an average yearly change.<br /><br />3. Don't use % decline. With regards to power calculations, just use mean change. I think G*Power would allow you to examine time by group interaction effects. <br /><br /><br /><br /><br /><br />Jeromy Anglimhttp://www.blogger.com/profile/12949204812496382042noreply@blogger.com