Tagged Questions

0
votes
1answer
30 views

EFA on R: Classifying Observations

I am newbie for R and Stats. I am using EFA in R [psych library] to identify the latent factors underlying my data. I got a reasonable amount of factors matching my purpose. My question is once I ...
2
votes
1answer
86 views

Comparing two logit or probit curves using a single parameter

I've conducted a psychological experiment on the same subject, under two different condition. For each condition I've collected the number of correct and wrong answer for each stimulus (number of ...
4
votes
1answer
222 views

IRT in R: Does anyone know of an IRT item calibration function that can cope with NA's?

I have a dataset that looks like this. ...
0
votes
2answers
88 views

Error message from grm() in ltm: subscript out of bounds

I am analyzing a survey data set. One of the items in the survey is: ...
1
vote
0answers
42 views

Omega H asymptotic

In the omega function in the psych package for R, we have several outputs including Hierarchical omega, Asymptotic omega and Total omega. I was reading about the outputs, but I find nothing about ...
1
vote
1answer
454 views

Understanding signficant interaction with non-significant main effects [duplicate]

Possible Duplicate: How to compute significant interaction estimates when main effect is not significant? I am an applied linguist and I am modelling responses to a vocabulary test taken by ...
2
votes
1answer
184 views

VSS criterion for the number of factors (in R's psych package)

I'm working from caracal's great example conducting a factor analysis on dichotomous data using R and I'm now struggling to understand the difference between VSS complexity 1 and VSS complexity 2 in ...
6
votes
1answer
722 views

Looking for a step through an example of a factor analysis on dichotomous data (binary variables) using R

I have some dichotomous data, only binary variables, and my boss asked me to perform a factor analysis using the tetrachoric correlations matrix. I’ve previously been able to teach myself how to run ...
2
votes
0answers
231 views

Fixing error variance in a path analysis to model measurement error in scales using sem package

I want to construct a path analysis model that can account for measurement error in totally aggregated parcels, which refer to parcels where all of the items in a scale are summed or averaged. If I am ...
3
votes
1answer
548 views

Which package to use for convergent and discriminant validity in R?

I am new to R and want to assess validity of some scales using R. Is there a package that I can use to test for convergent and discriminant validity in R?
1
vote
3answers
478 views

Is there a package in R which implements the weighted maximum likelihood method?

Is there a package in R which implements the weighted maximum likelihood method (Warm, 1996) for estimating the person parameters in Rasch Models?
8
votes
2answers
1k views

Recommended procedure for factor analysis on dichotomous data with R

I have to run a factor analysis on a dataset made up of dichotomous variables (0=yes, 1= no) and I don´t know if I'm on the right track. Using tetrachoric() I ...
20
votes
2answers
577 views

Detecting patterns of cheating on a multi-question exam

QUESTION: I have binary data on exam questions (correct/incorrect). Some individuals might have had prior access to a subset of questions and their correct answers. I don’t know who, how many, or ...
5
votes
2answers
765 views

Item Analysis for an R newbie

I am trying to assess a 20-item multliple choice test. I want to perform an item analysis such as can be found in this example. So for each question I want the P-value and the correlation with the ...
3
votes
1answer
420 views

R package ltm: How to manipulate title on item response category characteristic curve plot

I have conducted an IRT analysis using package ltm in R 2.10. fit1 <- grm(data) When producing plots of item response characteristic curves (ICCs), ...
5
votes
4answers
575 views

FA: Choosing Rotation matrix, based on “Simple Structure Criteria”

One of the most important issues in using factor analysis is its interpretation. Factor analysis often uses factor rotation to enhance its interpretation. After a satisfactory rotation, the rotated ...