-
1
-
-
0003478325
-
-
Cambridge, UK: MRC Biostatistics Unit, Institute of Public Health
-
Best, N., Cowles, M.K., & Vines, K. (1995). CODA: Convergence diagnosis and output analysis software for Gibbs sampling output Version 0.30 [computer program]. Cambridge, UK: MRC Biostatistics Unit, Institute of Public Health.
-
(1995)
CODA: Convergence diagnosis and output analysis software for Gibbs sampling output Version 0.30 [computer program]
-
-
Best, N.1
Cowles, M.K.2
Vines, K.3
-
5
-
-
0017764031
-
The ecology of adolescent activity and experience
-
Csikszentmihalyi, M., Larson, R., & Prescott, S. (1977). The ecology of adolescent activity and experience. Journal of Youth and Adolescence, 6(3), 281-294.
-
(1977)
Journal of Youth and Adolescence
, vol.6
, Issue.3
, pp. 281-294
-
-
Csikszentmihalyi, M.1
Larson, R.2
Prescott, S.3
-
6
-
-
0035534930
-
Bayesian estimation of a multilevel IRT model using Gibbs sampling
-
Fox, J.P., & Glas, C.A.W. (2001). Bayesian estimation of a multilevel IRT model using Gibbs sampling. Psychometrika, 66(2), 271-288.
-
(2001)
Psychometrika
, vol.66
, Issue.2
, pp. 271-288
-
-
Fox, J.P.1
Glas, C.A.W.2
-
7
-
-
0004012196
-
-
New York: Chapman & Hall
-
Gelman, A., Carlin, J.B., Stern, H.S., & Rubin, D.B. (1995). Bayesian data analysis. New York: Chapman & Hall.
-
(1995)
Bayesian data analysis
-
-
Gelman, A.1
Carlin, J.B.2
Stern, H.S.3
Rubin, D.B.4
-
8
-
-
0000954353
-
Efficient metropolis jumping rules
-
J.M. Bernardo, J.O. Berger, A.P. Dawid, & A.F.M. Smith (Eds.). New York: Oxford
-
Gelman, A., Roberts, G.O., & Gilks, W.R. (1996). Efficient Metropolis jumping rules. In J.M. Bernardo, J.O. Berger, A.P. Dawid, & A.F.M. Smith (Eds.), Bayesian statistics 5: Proceedings of the fifth Valencia international meeting (pp. 599-608). New York: Oxford.
-
(1996)
Bayesian statistics 5: Proceedings of the fifth Valencia international meeting
, pp. 599-608
-
-
Gelman, A.1
Roberts, G.O.2
Gilks, W.R.3
-
9
-
-
0001032163
-
Evaluating the accuracy of sampling-based approaches to calculating posterior moments
-
J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith (Eds.). Oxford, UK: Clarendon Press
-
Gweke, J. (1992). Evaluating the accuracy of sampling-based approaches to calculating posterior moments. In J.M. Bernardo, J.O. Berger, A.P. Dawid, and A.F.M. Smith (Eds.), Bayesian Statistics 4. Oxford, UK: Clarendon Press.
-
(1992)
Bayesian Statistics
, vol.4
-
-
Gweke, J.1
-
10
-
-
77956890234
-
Monte Carlo sampling methods using Markov chains and their applications
-
Hastings, W.K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97-109.
-
(1970)
Biometrika
, vol.57
, pp. 97-109
-
-
Hastings, W.K.1
-
12
-
-
84965572693
-
The analysis of social science data with missing values
-
Little, R., & Rubin, D. (1989). The analysis of social science data with missing values. Socio-logical Methods and Research, 18(2/3), 292-326.
-
(1989)
Socio-logical Methods and Research
, vol.18
, Issue.2-3
, pp. 292-326
-
-
Little, R.1
Rubin, D.2
-
15
-
-
0000261668
-
A Rasch model for partial credit scoring
-
Masters, G.N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174.
-
(1982)
Psychometrika
, vol.47
, Issue.2
, pp. 149-174
-
-
Masters, G.N.1
-
16
-
-
5744249209
-
Equations of state calculations by fast computing machines
-
Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., & Teller, E. (1953). Equations of state calculations by fast computing machines. The Journal of Chemical Physics, 21, 1087-1092.
-
(1953)
The Journal of Chemical Physics
, vol.21
, pp. 1087-1092
-
-
Metropolis, N.1
Rosenbluth, A.W.2
Rosenbluth, M.N.3
Teller, A.H.4
Teller, E.5
-
17
-
-
0033261632
-
Applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses
-
Patz, R.J., & Junker, B.W. (1999a). Applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses. Journal of Educational and Behavioral Statistics, 24(4), 342-366.
-
(1999)
Journal of Educational and Behavioral Statistics
, vol.24
, Issue.4
, pp. 342-366
-
-
Patz, R.J.1
Junker, B.W.2
-
18
-
-
0033411905
-
A straightforward approach to Markov Chain Monte Carlo methods for item response models
-
Patz, R.J., & Junker, B.W. (1999b). A straightforward approach to Markov Chain Monte Carlo methods for item response models. Journal of Educational and Behavioral Statistics, 24(2), 146-178.
-
(1999)
Journal of Educational and Behavioral Statistics
, vol.24
, Issue.2
, pp. 146-178
-
-
Patz, R.J.1
Junker, B.W.2
-
20
-
-
0017133178
-
Inference and missing data
-
Rubin, D.B. (1976). Inference and missing data. Biometrika, 63, 581-592.
-
(1976)
Biometrika
, vol.63
, pp. 581-592
-
-
Rubin, D.B.1
-
22
-
-
0030310752
-
Bayesian inference in applications of hierarchical models: Issues and methods
-
Seltzer, M., Wong, W.H., & Bryk, A.S. (1996). Bayesian inference in applications of hierarchical models: Issues and methods. Journal of Educational and Behavioral Statistics, 21, 131-167.
-
(1996)
Journal of Educational and Behavioral Statistics
, vol.21
, pp. 131-167
-
-
Seltzer, M.1
Wong, W.H.2
Bryk, A.S.3
-
23
-
-
0012101072
-
The quality of classroom experiences
-
M. Csikszentmihalyi & B. Schneider (Eds.). New York: Basic Books
-
Shernoff, D., Knauth, S., & Makris, E. (2000). The quality of classroom experiences. In M. Csikszentmihalyi & B. Schneider (Eds.), Becoming adult: How teenagers prepare for the world of work (pp. 141-164). New York: Basic Books.
-
(2000)
Becoming adult: How teenagers prepare for the world of work
, pp. 141-164
-
-
Shernoff, D.1
Knauth, S.2
Makris, E.3
-
24
-
-
0004213893
-
-
Chicago, IL: University of Chicago Press
-
Stodolsky, S. (1988). The subject matters. Chicago, IL: University of Chicago Press.
-
(1988)
The subject matters
-
-
Stodolsky, S.1
-
25
-
-
0001263082
-
Bayesian estimation in the Rasch model
-
Swaminathan, H., & Gifford, J.A. (1982). Bayesian estimation in the Rasch model. Journal of Educational Statistics, 7(3), 175-191.
-
(1982)
Journal of Educational Statistics
, vol.7
, Issue.3
, pp. 175-191
-
-
Swaminathan, H.1
Gifford, J.A.2
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