# eap: Function to estimate ability using EAP algorithm In talentlens/talentlens: R package for team TalentLens

## Description

Takes a named score vector and a data frame with known item parameters, and returns the estimated theta.

## Usage

 `1` ```eap(x, params, D = 1.702) ```

## Arguments

 `x` Vector with correct responses coded as 1 and incorrect responses as 0. NOTE: the values need to be named with item ids `params` Data frame with unique item names and corresponding item parameters on each row, NOTE: columns need to be named "id", "a", "b" and "c" `D` Scaling constant D (Defaults to 1.702 for normal ogive model)

## Details

The theta estimation algorithm is based on the implementation of the EAP algorithm in the GetFeedback platform. Instructions from Louis-Charles Vannier.

An alternative to using this function is `eapEst` from the `catR` package.

## Value

Estimated theta value.

## Author(s)

Morgan Strom

`eapEst` `eapSem`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```#Create named score vector score_vec <- c(1,1,0,1,0) names(score_vec) <- c("item1", "item2", "item3", "item4", "item5") #Create parameter data frame params <- data.frame(id = c("item1", "item2", "item3", "item4", "item5"), a = c(0.7, 0.8, 0.9, 1, 1.1), b = c(-2, -1, 0, 1, 2), c = c(0,0,0,0,0)) #Estimate theta theta <- eap(score_vec, params) #Using the function for a matrix with 4 observations score_mat <- matrix(c(1,1,0,1,0, 1,0,0,0,0, 1,1,1,1,0, 1,1,1,1,1), nrow = 4, ncol = 5, byrow = TRUE) colnames(score_mat) <- c("item1", "item2", "item3", "item4", "item5") thetas <- apply(score_mat, 1, eap, params=params) ```