rowBlockSum

blocksize

<p>(Optional) Vector for weighted sum</p>

<p>The original data set contains very long column headers. This function
does a keyword search over the headers to find those column headers that
match a particular keyword, e.g., mean, median, etc.</p>

Contains functions to perform various models and
methods for test equating. It currently implements the traditional
mean, linear and equipercentile equating methods, as well as the
mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods.
It also supports newest methods such that local equating, kernel
equating (using Gaussian, logistic and uniform kernels) with presmoothing,
and IRT parameter linking methods based on asymmetric item characteristic
functions. Functions to obtain both standard error of equating (SEE)
and standard error of equating difference between two equating
functions (SEED) are also implemented for the kernel method of
equating.

Jorge Burgos

SNSequate

rowBlockSum: Take a matrix and sum blocks of rows

Description

Usage

Arguments

Value