iqitemsR Documentation

16 multiple choice IQ items


16 multiple choice ability items taken from the Synthetic Aperture Personality Assessment (SAPA) web based personality assessment project. The data from 1525 subjects are included here as a demonstration set for scoring multiple choice inventories and doing basic item statistics. For more information on the development of an open source measure of cognitive ability, consult the readings available at the




A data frame with 1525 observations on the following 16 variables. The number following the name is the item number from SAPA.


Basic reasoning questions


Basic reasoning question


Basic reasoning question


Basic reasoning question


In the following alphanumeric series, what letter comes next?


In the following alphanumeric series, what letter comes next?


In the following alphanumeric series, what letter comes next


In the following alphanumeric series, what letter comes next?


A matrix reasoning task


A matrix reasoning task


A matrix reasoning task


A matrix reasoning task


Spatial Rotation of type 1.2


Spatial Rotation of type 1.2


Spatial Rotation of type 1.1


Spatial Rotation of type 2.3


16 items were sampled from 80 items given as part of the SAPA ( project (Revelle, Wilt and Rosenthal, 2009; Condon and Revelle, 2014) to develop online measures of ability. These 16 items reflect four lower order factors (verbal reasoning, letter series, matrix reasoning, and spatial rotations. These lower level factors all share a higher level factor ('g'). Similar data are available from the International Cognitive Abiity Resource at .

This data set and the associated data set (ability based upon scoring these multiple choice items and converting them to correct/incorrect may be used to demonstrate item response functions, tetrachoric correlations, or irt.fa as well as omega estimates of of reliability and hierarchical structure.

In addition, the data set is a good example of doing item analysis to examine the empirical response probabilities of each item alternative as a function of the underlying latent trait. When doing this, it appears that two of the matrix reasoning problems do not have monotonically increasing trace lines for the probability correct. At moderately high ability (theta = 1) there is a decrease in the probability correct from theta = 0 and theta = 2.


The example data set is taken from the Synthetic Aperture Personality Assessment personality and ability test at The data were collected with David Condon from 8/08/12 to 8/31/12.


Condon, David and Revelle, William, (2014) The International Cognitive Ability Resource: Development and initial validation of a public-domain measure. Intelligence, 43, 52-64.

Revelle, W., Wilt, J., and Rosenthal, A. (2010) Individual Differences in Cognition: New Methods for examining the Personality-Cognition Link In Gruszka, A. and Matthews, G. and Szymura, B. (Eds.) Handbook of Individual Differences in Cognition: Attention, Memory and Executive Control, Springer.

Revelle, W, Condon, D.M., Wilt, J., French, J.A., Brown, A., and Elleman, L.G. (2016) Web and phone based data collection using planned missing designs. In Fielding, N.G., Lee, R.M. and Blank, G. (Eds). SAGE Handbook of Online Research Methods (2nd Ed), Sage Publcations.


## Not run: 
iq.keys <- c(4,4,4, 6,  6,3,4,4,   5,2,2,4,   3,2,6,7)
score.multiple.choice(iq.keys,iqitems)   #this just gives summary statisics
#convert them to true false 
iq.scrub <- scrub(iqitems,isvalue=0)  #first get rid of the zero responses <-  score.multiple.choice(iq.keys,iq.scrub,score=FALSE) 
              #convert to wrong (0) and correct (1) for analysis
#see the ability data set for these analyses
#now, for some item analysis
#iq.irt <- irt.fa(  #do a basic irt <-score.irt(iq.irt,  #find the scores
#op <- par(mfrow=c(4,4))
#op <- par(mfrow=c(1,1))

## End(Not run)