EDMS 738: Bayesian Inference & Measurement Models

Intended Schedule, as of October 18, 2007

Fall 2007

Robert J. Mislevy

Class/Date

Topic

Readings

Assignment

Due Friday

#1

9/10

Introductions & Overview;

ECD models

"Psychometric Principles" pp. 1-25   BDA, Sections 1.1-1.6,1.8

BDA, Sections 1.7,1.9-1.11

BEIM, Ch 1

1 paragraph description of yourself

#2

9/17

Probability concepts; Intro to Bayes nets

Download MSBNx 

“Evidence & inference” pp. 1-45

DAR, Section 2.5

Probability review: DAR, 2.1- 2.5; BNEA, Ch. 2; BEIM, Ch 2

#3

9/24

Propagation in Bayes nets

Bayes nets examples

BNEA, 5.1& 5.2 ; 5.3 & 5.4

Edwards (1998) esp. 420-426

Re graphical models: BNEA, Ch. 4

#4

10/1

Cognitive diagnosis

“Role of prob-based inference in an ITS”

BNEA, Ch. 6; Ch 8

“Making sense of data…”

Bayes net problems

Download WinBUGS

#5

10/8

General Bayesian model / MCMC estimation 1

BNEA, 9.1; BUGS tutorial

BDA 2.6, 3.1-3.4, 14.1-14.2

BEIM Ch 3-5

#6

10/15

MCMC estimation 2

Student problem presentations begin

BNEA, 9.2, 9.3, & 9.5

Sindharay

BDA 11.1-11.6

#7

10/22

Classical Test Theory 1

"Psychometric Principles" pp. 26-38

DAR, Ch. 3, pp. 1-10; BEIM Ch 7

BUGS problems

#8

10/29

Classical Test Theory 2 Preposterior distributions

DAR, Ch. 3, pp. 10-21

Sindharay & Johnson; BDA 6.1-6.5, 6.7

DAR, Ch. 3, pp. 21-32

#9

11/5

Classical Test Theory 3 Preposterior distributions

DAR, Ch. 3, pp. 10-21

Sindharay & Johnson; BDA 6.1-6.5, 6.7

DAR, Ch. 3, pp. 21-32

  CTT assignment

#10

11/12

IRT 1

"Psychometric Principles" pp. 41-45

DAR, Ch. 4, pp. 1-10

#11

11/19

IRT 2

"Psychometric Principles" pp. 45-47 BEIM Ch 9

#12

11/26

Latent class analysis

BNEA, Ch 9, Sec 9.2, 9.3, & 9.5

BEIM 10  

  IRT assignment

#13

12/3

Factor analysis

BEIM 8  

#14

12/10

Missing data

BDA, Ch 21

Term Paper Due

12/19