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E-grāmata: Applied Measurement with jMetrik

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(University of Virginia, USA)
  • Formāts: 170 pages
  • Izdošanas datums: 13-Jun-2014
  • Izdevniecība: Routledge
  • ISBN-13: 9781136294167
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Applied Measurement with jMetrikPalielināt
  • Formāts: 170 pages
  • Izdošanas datums: 13-Jun-2014
  • Izdevniecība: Routledge
  • ISBN-13: 9781136294167
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jMetrik is a computer program for implementing classical and modern psychometric methods. It is designed to facilitate work in a production environment and to make advanced psychometric procedures accessible to every measurement practitioner. Applied Measurement with jMetrik reviews psychometric theory and describes how to use jMetrik to conduct a comprehensive psychometric analysis. Each chapter focuses on a topic in measurement, describes the steps for using jMetrik, and provides one or more examples of conducting an analysis on the topic. Recommendations and guidance for practice is provided throughout the book.

0.1 jMetrik graphical user interface xvi
0.2 Example dialog and interface components xvii
1.1 Import File selector
5(4)
1.2 Subset Cases dialog
9(8)
2.1 Basic item scoring with letters
17(1)
2.2 Basic item scoring with numbers
17(1)
2.3 Basic item scoring with letters and numbers
18(1)
2.4 Basic item scoring with binary and polytomous items
18(1)
2.5 Basic item scoring with alternate polytomous scoring
19(1)
2.6 Converting removing item scoring
19(1)
2.7 Basic item scoring with incorrect input
20(1)
2.8 Advanced Item Scoring dialog
21(1)
2.9 Advanced Item Scoring dialog example with special codes
22(1)
2.10 Multiple correct answers and advanced item scoring
23(1)
2.11 Collapsing categories with advanced item scoring
23(1)
2.12 Reverse scoring example
24(8)
3.1 Test Scaling dialog
32(2)
3.2 Linear Transformation dialog
34(1)
3.3 Rank Values dialog
35(1)
3.4 Histogram of exam1 sum scores
36(1)
3.5 Percentile rank table for exam1
37(1)
3.6 Line plot of percentile ranks
38(1)
3.7 Histogram of exam2 T-scores
39(7)
4.1 Item Analysis dialog
46(2)
4.2 Item analysis output for exam1
48(1)
4.3 Item Analysis dialog with two items removed from the analysis
49(1)
4.4 New Table Name dialog
50(1)
4.5 Example output table from an item analysis
50(1)
4.6 Exam2 item analysis results
51(13)
5.1 Reliability estimates, confidence intervals, and SEMs for exam1
64(1)
5.2 Reliability results for exam1 without bad items
65(1)
5.3 Decision consistency estimates
66(1)
5.4 CSEM output
66(1)
5.5 Reliability if Item Deleted output
67(3)
6.1 Plot of uniform DIF
70(1)
6.2 Plot of nonuniform DIF
70(6)
6.3 Cochran-Mantel-Haenszel DIF dialog
76(2)
6.4 DIF results for exam1 data
78(2)
6.5 DIF results for a mixed format test
80(1)
6.6 DIF results using a purified matching score
81(3)
7.1 Rasch model item characteristic curve
84(7)
7.2 Global Options tab
91(2)
7.3 Item Options tab
93(1)
7.4 Person Options tab
94(1)
7.5 Item difficulty and fit statistics for exam1 data
95(1)
7.6 Score table for exam1
96(1)
7.7 Scale quality statistics for exam1
97(3)
8.1 Option characteristic curves with widely spaced step parameters
100(1)
8.2 Options characteristic curves with narrowly spaced step parameters
101(1)
8.3 Options characteristic curves with a reversal
102(2)
8.4 Item difficulty estimates and fit statistics for exam3
104(1)
8.5 Category threshold estimates and fit statistics for exam3
105(1)
8.6 Item group codes in the Variables tab
106(1)
8.7 Item difficulty estimates and fit statistics for exam2
106(1)
8.8 Rating scale threshold estimates for exam2
107(2)
9.1 Item characteristic curves for three Rasch model items
109(1)
9.2 Option characteristic curves for a partial credit model item
110(1)
9.3 A test characteristic curve and test information function
110(1)
9.4 An item characteristic curve and item information function
111(2)
9.5 The item map for exam1 data
113(1)
9.6 IRT Plot dialog
114(2)
9.7 Nonparametric Characteristic Curves dialog
116(2)
9.8 A nonparametric item characteristic curve
118(1)
9.9 A nonparametric item characteristic curve for a miskeyed item
119(1)
9.10 Nonparametric curves for all response options on a binary item
120(1)
9.11 Nonparametric characteristic curves for a polytomous item
121(1)
9.12 Nonparametric curve for a DIF analysis
122(8)
10.1 Parameters tab in the Scale Linking dialog
130(2)
10.2 Transformation tab in the Scale Linking dialog
132(2)
10.3 IRT Score Equating dialog
134(1)
10.4 Common item summary tables for equating4 data
135(1)
10.5 Transformation coefficients
136(1)
10.6 Scale linking output for a mixed format test
137(1)
10.7 Score equating output for a mixed format test
138
TABLES
1.1 Naming conventions in jMetrik
4(6)
1.2 WHERE statement operators and descriptions
10(62)
6.1 2 x T contingency table for the kth stratum
72(45)
9.1 Kernel functions
117
J. Patrick Meyer is an associate professor in the Curry School of Education at the University of Virginia
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
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