similar to: Possible with lm() or glm()?

Dear R-Listers, to measure the psychometric curve of pitch discrimination, one sequentially presents two tones of slightly different pitch to an observer (animal will do), and asks "which is higher". The pschometric curve is the fraction of correct responses plotted against the pitch difference. It passes through 50% (pure guessing) at zero and normally approaches 100% at large

guRus and useRs, As I instruct my students: "With R what is difficult in anything else, is easy, usually one line of code; but, what is easy in anything else, is *&^%$%#$... (translation: next to impossible) in R." I just ran into such a case that has, to put it mildly, driven me to use spreadsheets (if that is not a sign of complete desperation, I don't know what is).

Hi John, Thank-you very much for replying, - in answer to your questions: *"As I understand what you wrote, all factors but linelabel are crossed, with linelabel nested within all the other factors?" That's exactly it, *" What is in the highest order cells? Single observations, or multiple scores?" I would say "single observations" - but i have to

Dear R users I have run an regression and want to extract the p value of the F statistics, but I can find a way to do that. x<-summary(lm(log(RV2)~log(IV.m),data=b)) Call: lm(formula = log(RV2) ~ log(IV.m), data = b[[11]]) Residuals: Min 1Q Median 3Q Max -0.26511 -0.09718 -0.01326 0.11095 0.29777 Coefficients: Estimate Std. Error t value Pr(>|t|)

R for OS X, version 2.0.1 Has the add parameter of plot commands been deprecated? It no longer occurs in the help listing for plot, and doesn't work, either. If it has been deprecated, what is the replacement? That is, how does one overlay an existing plot? -- John R. Vokey, PhD Professor B.E.R.G. - Behaviour and Evolution Research Group Micro-Cognition Laboratory Department of

useRs, A no doubt simple question, but I am baffled. Indeed, I think I once knew the answer, but can't recover it. The default contrasts for aov (and lm, and...) are contr.treatment and contr.poly for unordered and ordered factors, respectively. But, how does one invoke the latter? That is, in a data.frame, how does one indicate that a factor is an *ordered* factor such that

I have would like to use logistic regression to analyze the percentage of correct responses in a 2 alternative forced choice task. The question is whether one needs to take into account the fact expected probabilities for the percentage of correct responses ranges between 0.5 and 1 in this case and how to adjust the link function accordingly in R (see details below). Gabriel Subjects were asked

Hi, What package would you recommend for analyzing the validity/reliability of multiple choice tests. Doing things such as classical test analysis, factor analysis, item response theory. I've used psychometric (item.exam), MiscPsycho (alpha.Summary), and ltm (rcor.test). MiscPsycho reported the numbers most similar to what I get in SPSS: corrected point biserial correlations,

Dear all,  I hope this is the right place to ask this question. I am reviewing a research where the analyst(s) are using a linear regression model. The dependent variable (DV) is a continuous measure. The independent variables (IVs) are a mixture of linear and categorical variables. The author investigates whether performance (DV - continuous linear) is a function of age (continuous IV1 -

The following dummy data frame has factor Q (with 2 levels) nesting factor P (with levels p1 and p2 nested under q1, and p3 and p4 nested under q2), but both crossing the random variate s, which has 8 levels. The dependent measure is dv. > # The data frame: > testnest dv s P Q 1 1 s1 p1 q1 2 2 s2 p1 q1 3 1 s3 p1 q1 4 2 s4 p1 q1 5 1 s5 p1 q1 6 3 s6 p1 q1 7 3 s7

Dear R-helpers, I'm using a GLM with poisson errors to model integer count data as a function of one non-integer covariate. The model formula is: log(DV) ~ glm(log(IV,10),family=poisson). I'm getting a warning because the logged DV is no longer an integer. I have three questions: 1) Can I ignore the warning, or is logging the DV (resulting in non-integers) a serious violation of the

Hi everyone, I would like to introduce a new package: cNORM. It aims at solving problems with percentile estimation / norm score generation in biometrics and psychometrics, f. e. BMI growth curves, IQ tests ... Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables

Hi everyone, I would like to introduce a new package: cNORM. It aims at solving problems with percentile estimation / norm score generation in biometrics and psychometrics, f. e. BMI growth curves, IQ tests ... Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables

Hello folks, I have recently finished a pilot study of a survey and am working to complete the statistical analysis of the results in R. My Phd is technically in computer science (not statistics), although I teach basic stats and have a "decent" working knowledge of the area. With that said, my expertise in psychometrics theory and factor analysis is weaker, so I thought I would send an

Dear list: I'm hoping to tap in to the statistical expertise in the group, especially those familiar with simulation techniques. I'm finalizing a study where I obtain standard errors from two sources. The first source is a monte carlo simulation and the other source is an analytical model I have developed that appears to recover the standard errors from the simulation. All analysis are

Dear R-Experts, I was wondering how to fit a cumulative gaussian to a set of empirical data using R. On the R website as well as in the mail archives, I found a lot of help on how to fit a normal density function to empirical data, but unfortunately no advice on how to obtain reasonable estimates of m and sd for a gaussian ogive function. Specifically, I have data from a psychometric function

I am having trouble getting a loop to work for the following problem. Any help would be much appreciated. Thanks. I need to find the slope and intercept from the linear regression of Drug Level on Day by Participant. There are a total of 37 Participants. I need to store the Participant, Label, Slope, and Intercept in a new data frame. This data is ordered by Participant number 37 total

At any rate: Error(SUBJECT/IV) specifies two random effects: SUBJECT and SUBJECT:IV. This is most easily understood if you conceptually arrange your data in a SUBJECT x IV table: One effect is a set of random errors added to each row, the other is a set of effects added to each cell. If you have more than one observation within each cell, then you need a third set of errors to account for

Please can someone advise me how I can adjust correlations using bonferroni's correction? I am doing manny correlation tests as part of an investigation of the validity/reliability of a psychometric measure. Help would be so appreciated! Cheers, Louise

Pharmacokinetic and pharmacodynamic modeling and simulation By Dr. Jan Freijer September 24, 2009 Amsterdam, The Netherlands http://www.can.nl/events/details.php?id=57 This course is aimed at users of R or S-PLUS in the bio-pharmaceutical sciences who would like to use R for clinical trial simulations. topics include Working with packages in R - MASS -