| iqitems {psychTools} | R Documentation |
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 https://personality-project.org/.
data(iqitems)A data frame with 1525 observations on the following 16 variables. The number following the name is the item number from SAPA.
reason.4Basic reasoning questions
reason.16Basic reasoning question
reason.17Basic reasoning question
reason.19Basic reasoning question
letter.7In the following alphanumeric series, what letter comes next?
letter.33In the following alphanumeric series, what letter comes next?
letter.34In the following alphanumeric series, what letter comes next
letter.58In the following alphanumeric series, what letter comes next?
matrix.45A matrix reasoning task
matrix.46A matrix reasoning task
matrix.47A matrix reasoning task
matrix.55A matrix reasoning task
rotate.3Spatial Rotation of type 1.2
rotate.4Spatial Rotation of type 1.2
rotate.6Spatial Rotation of type 1.1
rotate.8Spatial Rotation of type 2.3
16 items were sampled from 80 items given as part of the SAPA (https://www.sapa-project.org/) 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 https://www.icar-project.org/ .
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 https://www.sapa-project.org/. 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, William, Dworak, Elizabeth M. and Condon, David (2020) Cognitive ability in everyday life: the utility of open-source measures. Current Directions in Psychological Science, 29, (4) 358-363. Open access at \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0963721420922178")}.
Dworak, Elizabeth M., Revelle, William, Doebler, Philip and Condon, David (2021) Using the International Cognitive Ability Resource as an open source tool to explore individual differences in cognitive ability. Personality and Individual Differences, 169. Open access at \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.paid.2020.109906")}.
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.
data(iqitems)
iq.keys <- c(4,4,4, 6, 6,3,4,4, 5,2,2,4, 3,2,6,7)
psych::score.multiple.choice(iq.keys,iqitems) #this just gives summary statisics
#convert them to true false
iq.scrub <- psych::scrub(iqitems,isvalue=0) #first get rid of the zero responses
iq.tf <- psych::score.multiple.choice(iq.keys,iq.scrub,score=FALSE)
#convert to wrong (0) and correct (1) for analysis
psych::describe(iq.tf)
#see the ability data set for these analyses
#now, for some item analysis
iq.irt <- psych::irt.fa(iq.tf) #do a basic irt
iq.sc <- psych::scoreIrt(iq.irt,iq.tf) #find the scores
op <- par(mfrow=c(4,4))
psych::irt.responses(iq.sc[,1], iq.tf)
op <- par(mfrow=c(1,1))