A Latent Ability Model for Count Data and Application to Processing Speed

被引：14

作者：

Doebler, Anna ^{[1
]}

Doebler, Philipp ^{[1
]}

Holling, Heinz ^{[1
]}

机构：

[1] Univ Munster, D-48149 Munster, Germany

来源：

APPLIED PSYCHOLOGICAL MEASUREMENT | 2014年 / 38卷 / 08期

关键词：

count data; Rasch Poisson counts model; item characteristic curve; processing speed; MULTIPLICATIVE POISSON MODEL; ALGORITHM; ACCURACY;

D O I：

10.1177/0146621614543513

中图分类号：

O1 [数学]; C [社会科学总论];

学科分类号：

03 ; 0303 ; 0701 ; 070101 ;

摘要：

A new family of item response theory models for count data, based on item characteristic curves (ICCs) of binary models, is presented. These models assume a Poisson distribution for the observed scores where the mean is given by the product of a speed parameter and an ICC, for example, the curve of the one- or two-parameter logistic model. Joint and marginal maximum likelihood parameter estimations are discussed and the proposed procedures are evaluated by computer simulation. As an application, item level data from a test measuring processing speed are analyzed and item fit and test information are explored.

引用

页码：587 / 598

页数：12

共 50 条

[1] Latent class model with two latent variables for analysis of count data
Yamaguchi, Kazunori
Sakurai, Naoko
Watanabe, Michiko
[J]. COMPSTAT 2006: PROCEEDINGS IN COMPUTATIONAL STATISTICS, 2006, : 395 - +
[2] Understanding Ability and Reliability Differences Measured with Count Items: The Distributional Regression Test Model and the Count Latent Regression Model
Beisemann, Marie
Forthmann, Boris
Doebler, Philipp
[J]. MULTIVARIATE BEHAVIORAL RESEARCH, 2024, 59 (03) : 502 - 522
[3] A latent process regression model for spatially correlated count data
McShane, LM
Albert, PS
Palmatier, MA
[J]. BIOMETRICS, 1997, 53 (02) : 698 - 706
[4] A LATENT CLASS POISSON REGRESSION-MODEL FOR HETEROGENEOUS COUNT DATA
WEDEL, M
DESARBO, WS
BULT, JR
RAMASWAMY, V
[J]. JOURNAL OF APPLIED ECONOMETRICS, 1993, 8 (04) : 397 - 411
[5] A Bayesian latent process spatiotemporal regression model for areal count data
Utazi, C. Edson
Afuecheta, Emmanuel O.
Nnanatu, C. Christopher
[J]. SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY, 2018, 25 : 25 - 37
[6] A conditional count model for repeated count data and its application to GEE approach
Rajib Dey
M. Ataharul Islam
[J]. Statistical Papers, 2017, 58 : 485 - 504
[7] A conditional count model for repeated count data and its application to GEE approach
Dey, Rajib
Islam, M. Ataharul
[J]. STATISTICAL PAPERS, 2017, 58 (02) : 485 - 504
[8] A new count data model with application in genetics and ecology
Rashid, Adil
Ahmad, Zahoor
Jan, T. R.
[J]. ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS, 2016, 9 (01) : 213 - 226
[9] Latent feature regression for multivariate count data
Klami, Arto
Tripathi, Abhishek
Sirola, Johannes
Vare, Lauri
Roulland, Frederic
[J]. ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 38, 2015, 38 : 462 - 470
[10] TRANSLATION SPEED AND INFORMATION PROCESSING ABILITY
GEKOSKI, WL
[J]. CANADIAN PSYCHOLOGIST-PSYCHOLOGIE CANADIENNE, 1970, 11 (02): : 185 - &

← 1 2 3 4 5 →