Quant_13B_problem_dataList {TestGardener}

List of objects essential for an analysis of the abbreviated SweSAT Quantitative multiple choice test.

Description

The data are for 1000 randomly selected examinees taking 24 math analysis multiple choice questions.

Usage

Quant_13B_problem_dataList

Format

A named list.

Details

A named list with 19 members:

chcemat:

A matrix of response data with N rows and n columns where N is the number of examinees or respondents and n is the number of items. Entries in the matrices are the indices of the options chosen. Column i of chcemat is expected to contain only the integers 1,...,noption.

key:

If the data are from a test of the multiple choices type where the right answer is scored 1 and the wrong answers 0, this is a numeric vector of length n containing the indices the right answers. Otherwise, it is NULL.

titlestr:

A string containing a title for the analysis.

N:

The number of persons tested

n:

The number of questons or items

noption:

A numeric vector of length n containing the numbers of options for each item.

Sdim:

The total dimension of the surprisal scores.

grbgvec:

A vector of length indicating which option for each item contains missing or illegal choice values. If 0, there is no such option.

ScoreList:

A list vector or length n with each object a numeric vector of weights assigned to each option for each item.

nbin:

The number of bins for binning the data.

NumBasis:

The number of spline basis functions.

Sbasis:

An basisfd object for the defining the surprisal curves.

itemlabvec:

A character vector with a title string for each item.

optlabList:

A list vector of length n with a character vector of labels for each object within each item.

scrvec:

A vector of length N containing the examinee or respondent sum scores.

itmvec:

A vector of length n containing the item sum scores.

scrjit:

A numeric vector of length N containing small jitters to each sum score to break up ties,

sumscr_rng:

A vector of length 2 containing the limits of observed sum scores.

SfdList:

A list vector containing essential objects for each item.

scrfine:

A fine mesh of test score values for plotting.

indexQnt:

A numeric vector of length 2*nbin + 1 containing the bin boundaries alternating with the bin centers. These are initially defined as seq(0,100,len=2*nbin+1).

percntrnk:

A vector length N containing the sum score percentile ranks.

PcntMarkers:

The marker percentages for plotting: 5, 25, 50, 75 and 95.