-
1
-
-
84892280454
-
Bayesian computation with R
-
New York, NY: Springer.
-
Albert, J. (2009). Bayesian computation with R. New York, NY: Springer. http://dx.doi.org/10.1007/978-0-387-92298-0
-
(2009)
-
-
Albert, J.1
-
2
-
-
67349219753
-
Amos (Version 7.0) [Computer program]
-
Chicago, IL: SPSS
-
Arbuckle, J. L. (2006). Amos (Version 7.0) [Computer program]. Chicago, IL: SPSS.
-
(2006)
-
-
Arbuckle, J.L.1
-
3
-
-
84865304109
-
Bayesian analysis using Mplus: Technical implementation
-
Tech. Rep. No. Version 3.
-
Asparouhov, T., & Muthén, B. (2010). Bayesian analysis using Mplus: Technical implementation. Tech. Rep. No. Version 3. https://www .statmodel.com/download/Bayes3.pdf
-
(2010)
-
-
Asparouhov, T.1
Muthén, B.2
-
4
-
-
84867176040
-
The case for objective Bayesian analysis
-
Berger, J. (2006). The case for objective Bayesian analysis. Bayesian Analysis, 3, 385-402.
-
(2006)
Bayesian Analysis
, vol.3
, pp. 385-402
-
-
Berger, J.1
-
5
-
-
77956802446
-
Bayesian forecasting of immigration to selected European countries by using expert knowledge
-
Bijak, J., & Wisniowski, A. (2010). Bayesian forecasting of immigration to selected European countries by using expert knowledge. Journal of the Royal Statistical Society Series A, 173, 775-796. http://dx.doi.org/10 .1111/j.1467-985X.2009.00635.x
-
(2010)
Journal of the Royal Statistical Society Series A
, vol.173
, pp. 775-796
-
-
Bijak, J.1
Wisniowski, A.2
-
6
-
-
84889410130
-
Introduction to Bayesian statistics
-
New York, NY: Wiley.
-
Bolstad, W. M. (2007). Introduction to Bayesian statistics. New York, NY: Wiley. http://dx.doi.org/10.1002/9780470181188
-
(2007)
-
-
Bolstad, W.M.1
-
7
-
-
0043096621
-
Convergence assessment techniques for Markov chain Monte Carlo
-
Brooks, S. P., & Roberts, G. O. (1998). Convergence assessment techniques for Markov chain Monte Carlo. Statistics and Computing, 8, 319-335. http://dx.doi.org/10.1023/A:1008820505350
-
(1998)
Statistics and Computing
, vol.8
, pp. 319-335
-
-
Brooks, S.P.1
Roberts, G.O.2
-
8
-
-
68649116880
-
In-season prediction of batting averages: A field test of empirical Bayes and Bayes methodologies
-
Brown, L. D. (2008). In-season prediction of batting averages: A field test of empirical Bayes and Bayes methodologies. The Annals of Applied Statistics, 2, 113-152. http://dx.doi.org/10.1214/07-AOAS138
-
(2008)
The Annals of Applied Statistics
, vol.2
, pp. 113-152
-
-
Brown, L.D.1
-
9
-
-
4143139214
-
MCMC Estimation in MLwiN v2.1
-
Bristol, UK: Centre for Multilevel Modelling, University of Bristol
-
Browne, W. J. (2009). MCMC Estimation in MLwiN v2.1. Bristol, UK: Centre for Multilevel Modelling, University of Bristol.
-
(2009)
-
-
Browne, W.J.1
-
10
-
-
0142200381
-
Performance of empirical Bayes estimators of level-2 random parameters in multilevel analysis: A Monte Carlo study for longitudinal designs
-
Candel, J. J. M., & Winkens, B. (2003). Performance of empirical Bayes estimators of level-2 random parameters in multilevel analysis: A Monte Carlo study for longitudinal designs. Journal of Educational and Behavioral Statistics, 28, 169 -194. http://dx.doi.org/10.3102/ 10769986028002169
-
(2003)
Journal of Educational and Behavioral Statistics
, vol.28
, pp. 169 -194
-
-
Candel, J.J.M.1
Winkens, B.2
-
11
-
-
59749104832
-
Bayesian methods for data analysis
-
Boca Raton, FL: Chapman and Hall/CRC Press
-
Carlin, B. P., & Louis, T. A. (2009). Bayesian methods for data analysis. Boca Raton, FL: Chapman and Hall/CRC Press.
-
(2009)
-
-
Carlin, B.P.1
Louis, T.A.2
-
13
-
-
85147609234
-
Bayesian ideas and data analysis: An introduction for scientists and statisticians
-
Boca Raton, FL: CRC Press
-
Christensen, R., Johnson, W. O., Branscum, A. J., & Hanson, T. E. (2010). Bayesian ideas and data analysis: An introduction for scientists and statisticians. Boca Raton, FL: CRC Press.
-
(2010)
-
-
Christensen, R.1
Johnson, W.O.2
Branscum, A.J.3
Hanson, T.E.4
-
14
-
-
84879539198
-
Bayesian methods for data-dependent priors (Doctoral Dissertation)
-
Ohio State University, Columbus, OH
-
Darnieder, W. F. (2011). Bayesian methods for data-dependent priors (Doctoral Dissertation). Ohio State University, Columbus, OH.
-
(2011)
-
-
Darnieder, W.F.1
-
15
-
-
84861637571
-
Measurement and structural model class separation in mixture-CFA: ML/EM versus MCMC
-
Depaoli, S. (2012). Measurement and structural model class separation in mixture-CFA: ML/EM versus MCMC. Structural Equation Modeling, 19, 178-203. http://dx.doi.org/10.1080/10705511.2012.659614
-
(2012)
Structural Equation Modeling
, vol.19
, pp. 178-203
-
-
Depaoli, S.1
-
16
-
-
84879532581
-
Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation
-
Depaoli, S. (2013). Mixture class recovery in GMM under varying degrees of class separation: Frequentist versus Bayesian estimation. Psychological Methods, 18, 186-219. http://dx.doi.org/10.1037/a0031609
-
(2013)
Psychological Methods
, vol.18
, pp. 186-219
-
-
Depaoli, S.1
-
17
-
-
84898064791
-
The impact of inaccurate "informative" priors for growth parameters in Bayesian Growth Mixture Modeling
-
Depaoli, S. (2014). The impact of inaccurate "informative" priors for growth parameters in Bayesian Growth Mixture Modeling. Structural Equation Modeling, 21, 239-252. http://dx.doi.org/10.1080/10705511 .2014.882686
-
(2014)
Structural Equation Modeling
, vol.21
, pp. 239-252
-
-
Depaoli, S.1
-
18
-
-
84925856390
-
Linear and nonlinear growth models: Describing a Bayesian perspective
-
Depaoli, S., & Boyajian, J. (2014). Linear and nonlinear growth models: Describing a Bayesian perspective. Journal of Consulting and Clinical Psychology, 82, 784-802. http://dx.doi.org/10.1037/a0035147
-
(2014)
Journal of Consulting and Clinical Psychology
, vol.82
, pp. 784-802
-
-
Depaoli, S.1
Boyajian, J.2
-
19
-
-
84930577404
-
A Bayesian approach to multilevel structural equation modeling with continuous and dichotomous outcomes
-
Depaoli, S., & Clifton, J. (2015). A Bayesian approach to multilevel structural equation modeling with continuous and dichotomous outcomes. Structural Equation Modeling, 22, 327-351. http://dx.doi.org/10 .1080/10705511.2014.937849
-
(2015)
Structural Equation Modeling
, vol.22
, pp. 327-351
-
-
Depaoli, S.1
Clifton, J.2
-
20
-
-
84991101408
-
Improving transparency and replication in Bayesian statistics: The WAMBS-checklist
-
Psychological Methods
-
Depaoli, S., & van de Schoot, R. (2016). Improving transparency and replication in Bayesian statistics: The WAMBS-checklist. Psychological Methods.
-
(2016)
-
-
Depaoli, S.1
van de Schoot, R.2
-
21
-
-
84977123320
-
Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: Implementation and discussion
-
Depaoli, S., van de Schoot, R., van Loey, N., & Sijbrandij, M. (2015). Using Bayesian statistics for modeling PTSD through Latent Growth Mixture Modeling: Implementation and discussion. European Journal of Psychotraumatology, 6, 27516. http://dx.doi.org/10.3402/ejpt.v6.27516
-
(2015)
European Journal of Psychotraumatology
, vol.6
, pp. 27516
-
-
Depaoli, S.1
van de Schoot, R.2
van Loey, N.3
Sijbrandij, M.4
-
22
-
-
80051815956
-
Bayesian versus orthodox statistics: Which side are you on?
-
Dienes, Z. (2011). Bayesian versus orthodox statistics: Which side are you on? Perspectives on Psychological Science, 6, 274-290. http://dx.doi .org/10.1177/1745691611406920
-
(2011)
Perspectives on Psychological Science
, vol.6
, pp. 274-290
-
-
Dienes, Z.1
-
23
-
-
81255172001
-
Advanced Reach Tool (ART): Development of the mechanistic model
-
Fransman, W., Van Tongeren, M., Cherrie, J. W., Tischer, M., Schneider, T., Schinkel, J., Tielemans, E. (2011). Advanced Reach Tool (ART): Development of the mechanistic model. The Annals of Occupational Hygiene, 55, 957-979. http://dx.doi.org/10.1093/annhyg/mer083
-
(2011)
The Annals of Occupational Hygiene
, vol.55
, pp. 957-979
-
-
Fransman, W.1
Van Tongeren, M.2
Cherrie, J.W.3
Tischer, M.4
Schneider, T.5
Schinkel, J.6
Tielemans, E.7
-
24
-
-
84867086419
-
Prior distributions for variance parameters in hierarchical models
-
Gelman, A. (2006a). Prior distributions for variance parameters in hierarchical models. Bayesian Analysis, 1, 515-533. http://dx.doi.org/10.1214/ 06-BA117A
-
(2006)
Bayesian Analysis
, vol.1
, pp. 515-533
-
-
Gelman, A.1
-
25
-
-
85020265292
-
Modeling the group-level covariance matrix for varying-intercept, varying-slope multilevel models: Updated paper by O'Malley and Zaslavsky
-
Gelman, A. (2006b). Modeling the group-level covariance matrix for varying-intercept, varying-slope multilevel models: Updated paper by O'Malley and Zaslavsky. Retrieved from http://andrewgelman.com/ 2006/09/01/modeling_the_gr/
-
(2006)
-
-
Gelman, A.1
-
26
-
-
0030328027
-
Physiological pharmacokinetic analysis using population modeling and informative prior distributions
-
Gelman, A., Bois, F., & Jiang, J. (1996). Physiological pharmacokinetic analysis using population modeling and informative prior distributions. Journal of the American Statistical Association, 91, 1400-1412. http:// dx.doi.org/10.1080/01621459.1996.10476708
-
(1996)
Journal of the American Statistical Association
, vol.91
, pp. 1400-1412
-
-
Gelman, A.1
Bois, F.2
Jiang, J.3
-
27
-
-
0004012196
-
Bayesian data analysis (2nd ed.)
-
London, UK: Chapman & Hall
-
Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B. (2004). Bayesian data analysis (2nd ed.). London, UK: Chapman & Hall.
-
(2004)
-
-
Gelman, A.1
Carlin, J.B.2
Stern, H.S.3
Rubin, D.B.4
-
28
-
-
33845601607
-
Data analysis using regression and multilevel/ hierarchical models
-
New York, NY: Cambridge University Press
-
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/ hierarchical models. New York, NY: Cambridge University Press.
-
(2007)
-
-
Gelman, A.1
Hill, J.2
-
29
-
-
84865371361
-
A weakly informative default prior distribution for logistic and other regression models
-
Gelman, A., Jakulin, A., Pittau, M. G., & Su, Y.-S. (2008). A weakly informative default prior distribution for logistic and other regression models. The Annals of Applied Statistics, 2, 1360-1383. http://dx.doi .org/10.1214/08-AOAS191
-
(2008)
The Annals of Applied Statistics
, vol.2
, pp. 1360-1383
-
-
Gelman, A.1
Jakulin, A.2
Pittau, M.G.3
Su, Y.-S.4
-
30
-
-
84972492387
-
Inference from iterative simulation using multiple sequences
-
Gelman, A., & Rubin, D. B. (1992a). Inference from iterative simulation using multiple sequences. Statistical Science, 7, 457-472. http://dx.doi .org/10.1214/ss/1177011136
-
(1992)
Statistical Science
, vol.7
, pp. 457-472
-
-
Gelman, A.1
Rubin, D.B.2
-
31
-
-
0001032162
-
A single series from the Gibbs sampler provides a false sense of security
-
In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Oxford, NY: Oxford University Press.
-
Gelman, A., & Rubin, D. B. (1992b). A single series from the Gibbs sampler provides a false sense of security. In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 625-631). Oxford, NY: Oxford University Press.
-
(1992)
Bayesian statistics
, vol.4
, pp. 625-631
-
-
Gelman, A.1
Rubin, D.B.2
-
33
-
-
0021518209
-
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
-
Geman, S., & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. Pattern Analysis and Machine Intelligence, 6, 721-741.
-
(1984)
Pattern Analysis and Machine Intelligence
, vol.6
, pp. 721-741
-
-
Geman, S.1
Geman, D.2
-
34
-
-
0001032163
-
Evaluating the accuracy of sampling-based approaches to calculating posterior moments
-
In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.) Oxford, UK: Oxford University Press
-
Geweke, J. (1992). Evaluating the accuracy of sampling-based approaches to calculating posterior moments. In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 169-193). Oxford, UK: Oxford University Press.
-
(1992)
Bayesian statistics
, vol.4
, pp. 169-193
-
-
Geweke, J.1
-
36
-
-
0007833410
-
Bayesian methods: A social and behavioral sciences approach
-
Boca Raton, FL: CRC Press
-
Gill, J. (2008). Bayesian methods: A social and behavioral sciences approach. Boca Raton, FL: CRC Press.
-
(2008)
-
-
Gill, J.1
-
37
-
-
84873406535
-
Sensitivity analyses for sparse-data problems-using weakly informative Bayesian priors
-
Hamra, G. B., MacLehose, R. F., & Cole, S. R. (2013). Sensitivity analyses for sparse-data problems-using weakly informative Bayesian priors. Epidemiology, 24, 233-239. http://dx.doi.org/10.1097/EDE .0b013e318280db1d
-
(2013)
Epidemiology
, vol.24
, pp. 233-239
-
-
Hamra, G.B.1
MacLehose, R.F.2
Cole, S.R.3
-
38
-
-
0020850136
-
Simulation run length control in the presence of an initial transient
-
Heidelberger, P., & Welch, P. D. (1983). Simulation run length control in the presence of an initial transient. Operations Research, 31, 1109- 1144. http://dx.doi.org/10.1287/opre.31.6.1109
-
(1983)
Operations Research
, vol.31
, pp. 1109- 1144
-
-
Heidelberger, P.1
Welch, P.D.2
-
39
-
-
84889666279
-
Bayesian methodology to estimate and update safety performance functions under limited data conditions: A sensitivity analysis
-
Heydari, S., Miranda-Moreno, L. F., Lord, D., & Fu, L. (2014). Bayesian methodology to estimate and update safety performance functions under limited data conditions: A sensitivity analysis. Accident Analysis and Prevention, 64, 41-51. http://dx.doi.org/10.1016/j.aap.2013.11.001
-
(2014)
Accident Analysis and Prevention
, vol.64
, pp. 41-51
-
-
Heydari, S.1
Miranda-Moreno, L.F.2
Lord, D.3
Fu, L.4
-
40
-
-
0034263752
-
The proof of the pudding: An illustration of the relative strengths of null hypothesis, meta-analysis, and Bayesian analysis
-
Howard, G. S., Maxwell, S. E., & Fleming, K. J. (2000). The proof of the pudding: An illustration of the relative strengths of null hypothesis, meta-analysis, and Bayesian analysis. Psychological Methods, 5, 315- 332. http://dx.doi.org/10.1037/1082-989X.5.3.315
-
(2000)
Psychological Methods
, vol.5
, pp. 315- 332
-
-
Howard, G.S.1
Maxwell, S.E.2
Fleming, K.J.3
-
41
-
-
84883641307
-
How few countries will do?Comparative survey analysis from a Bayesian perspective
-
Hox, J., van de Schoot, R., & Matthijsse, S. (2012). How few countries will do? Comparative survey analysis from a Bayesian perspective. Survey Research Methods, 6, 87-93.
-
(2012)
Survey Research Methods
, vol.6
, pp. 87-93
-
-
Hox, J.1
van de Schoot, R.2
Matthijsse, S.3
-
42
-
-
84946711386
-
Bayesian survival analysis
-
New York, NY: Wiley.
-
Ibrahim, J. G., Chen, M. H., & Sinha, D. (2005). Bayesian survival analysis. New York, NY: Wiley. http://dx.doi.org/10.1002/0470011815 .b2a11006
-
(2005)
-
-
Ibrahim, J.G.1
Chen, M.H.2
Sinha, D.3
-
43
-
-
65549126972
-
Bayesian analysis for the social sciences
-
New York, NY: Wiley.
-
Jackman, S. (2009). Bayesian analysis for the social sciences (Vol. 846). New York, NY: Wiley. http://dx.doi.org/10.1002/9780470686621
-
(2009)
, vol.846
-
-
Jackman, S.1
-
44
-
-
0003414592
-
Theory of probability, 3rd ed
-
New York: Oxford University Press
-
Jeffreys, H. (1961). Theory of probability, 3rd ed. New York: Oxford University Press.
-
(1961)
-
-
Jeffreys, H.1
-
45
-
-
84885037441
-
Uniformly most powerful Bayesian tests
-
Johnson, V. E. (2013). Uniformly most powerful Bayesian tests. Annals of Statistics, 41, 1716-1741. http://dx.doi.org/10.1214/13-AOS1123
-
(2013)
Annals of Statistics
, vol.41
, pp. 1716-1741
-
-
Johnson, V.E.1
-
46
-
-
32844456565
-
Methodological advances in the analysis of individual growth with relevance to education policy
-
Kaplan, D. (2002). Methodological advances in the analysis of individual growth with relevance to education policy. Peabody Journal of Education, 77, 189-215. http://dx.doi.org/10.1207/S15327930PJE7704_9
-
(2002)
Peabody Journal of Education
, vol.77
, pp. 189-215
-
-
Kaplan, D.1
-
47
-
-
84926418781
-
Bayesian statistics for the social sciences
-
New York, NY: Guilford Press
-
Kaplan, D. (2014). Bayesian statistics for the social sciences. New York, NY: Guilford Press.
-
(2014)
-
-
Kaplan, D.1
-
48
-
-
84880720332
-
Bayesian structural equation modeling
-
In R. Hoyle (Ed.), New York, NY: Guilford Press.
-
Kaplan, D., & Depaoli, S. (2012). Bayesian structural equation modeling. In R. Hoyle (Ed.), Handbook of structural equation modeling (pp. 650-673). New York, NY: Guilford Press.
-
(2012)
Handbook of structural equation modeling
, pp. 650-673
-
-
Kaplan, D.1
Depaoli, S.2
-
49
-
-
85143949056
-
Bayesian statistical methods
-
In T. D. Little (Ed.), Oxford, UK: Oxford University Press.
-
Kaplan, D., & Depaoli, S. (2013). Bayesian statistical methods. In T. D. Little (Ed.), Oxford handbook of quantitative methods (pp. 407-437). Oxford, UK: Oxford University Press.
-
(2013)
Oxford handbook of quantitative methods
, pp. 407-437
-
-
Kaplan, D.1
Depaoli, S.2
-
50
-
-
36148959043
-
Estimating item response theory models using Markov Chain Monte Carlo methods
-
Kim, J. S., & Bolt, D. M. (2007). Estimating item response theory models using Markov Chain Monte Carlo methods. Educational Measurement: Issues and Practice, 26, 38-51. http://dx.doi.org/10.1111/j.1745-3992 .2007.00107.x
-
(2007)
Educational Measurement: Issues and Practice
, vol.26
, pp. 38-51
-
-
Kim, J.S.1
Bolt, D.M.2
-
51
-
-
84880956938
-
Single and multiple ability estimation in the SEM framework: A noninformative Bayesian estimation approach
-
Kim, S. Y., Suh, Y., Kim, J. S., Albanese, M. A., & Langer, M. M. (2013). Single and multiple ability estimation in the SEM framework: A noninformative Bayesian estimation approach. Multivariate Behavioral Research, 48, 563-591. http://dx.doi.org/10.1080/00273171.2013.802647
-
(2013)
Multivariate Behavioral Research
, vol.48
, pp. 563-591
-
-
Kim, S.Y.1
Suh, Y.2
Kim, J.S.3
Albanese, M.A.4
Langer, M.M.5
-
52
-
-
77954032966
-
Doing Bayesian analysis
-
Burlington, MA: Academic Press
-
Kruschke, J. K. (2010). Doing Bayesian analysis. Burlington, MA: Academic Press.
-
(2010)
-
-
Kruschke, J.K.1
-
53
-
-
80051812703
-
Introduction to special section on Bayesian data analysis
-
Kruschke, J. K. (2011). Introduction to special section on Bayesian data analysis. Perspectives on Psychological Science, 6, 272-273. http://dx .doi.org/10.1177/1745691611406926
-
(2011)
Perspectives on Psychological Science
, vol.6
, pp. 272-273
-
-
Kruschke, J.K.1
-
54
-
-
23244434820
-
How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS
-
Lambert, P. C., Sutton, A. J., Burton, P. R., Abrams, K. R., & Jones, D. R. (2005). How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS. Statistics in Medicine, 24, 2401-2428. http://dx.doi.org/10.1002/sim.2112
-
(2005)
Statistics in Medicine
, vol.24
, pp. 2401-2428
-
-
Lambert, P.C.1
Sutton, A.J.2
Burton, P.R.3
Abrams, K.R.4
Jones, D.R.5
-
55
-
-
84920841704
-
Structural equation modeling: A Bayesian approach
-
West Sussex, UK: Wiley and Sons.
-
Lee, S.-Y. (2007). Structural equation modeling: A Bayesian approach. West Sussex, UK: Wiley and Sons. http://dx.doi.org/10.1002/ 9780470024737
-
(2007)
-
-
Lee, S.-Y.1
-
56
-
-
84867407667
-
On thinning of chains in MCMC
-
Link, W. A., & Eaton, M. J. (2012). On thinning of chains in MCMC. Methods in Ecology and Evolution, 3, 112-115. http://dx.doi.org/10 .1111/j.2041-210X.2011.00131.x
-
(2012)
Methods in Ecology and Evolution
, vol.3
, pp. 112-115
-
-
Link, W.A.1
Eaton, M.J.2
-
57
-
-
80051716562
-
Confronting prior convictions: On issues of prior sensitivity and likelihood robustness in Bayesian analysis
-
Lopes, H. F., & Tobias, J. L. (2011). Confronting prior convictions: On issues of prior sensitivity and likelihood robustness in Bayesian analysis. Annual Review of Economics, 3, 107-131. http://dx.doi.org/10.1146/ annurev-economics-111809-125134
-
(2011)
Annual Review of Economics
, vol.3
, pp. 107-131
-
-
Lopes, H.F.1
Tobias, J.L.2
-
58
-
-
84930642183
-
-
Love, J., Selker, R., Marsman, M., Jamil, T., Verhagen, A. J., Ly, A., Wagenmakers, E.-J. (2015). JASP (Version 0.6.6) [Computer software].
-
(2015)
JASP (Version 0.6.6) [Computer software].
-
-
Love, J.1
Selker, R.2
Marsman, M.3
Jamil, T.4
Verhagen, A.J.5
Ly, A.6
Wagenmakers, E.-J.7
-
59
-
-
0006407254
-
Win- BUGS-A Bayesian modelling framework: Concepts, structure, and extensibility
-
Lunn, D. J., Thomas, A., Best, N., & Spiegelhalter, D. (2000). Win- BUGS-A Bayesian modelling framework: Concepts, structure, and extensibility. Statistics and Computing, 10, 325-337. http://dx.doi.org/ 10.1023/A:1008929526011
-
(2000)
Statistics and Computing
, vol.10
, pp. 325-337
-
-
Lunn, D.J.1
Thomas, A.2
Best, N.3
Spiegelhalter, D.4
-
60
-
-
56249115275
-
Introduction to applied Bayesian statistics and estimation for social scientists
-
New York, NY: Springer.
-
Lynch, S. M. (2007). Introduction to applied Bayesian statistics and estimation for social scientists (Vol. 2). New York, NY: Springer. http://dx.doi.org/10.1007/978-0-387-71265-9
-
(2007)
, vol.2
-
-
Lynch, S.M.1
-
61
-
-
84856318176
-
Eliciting expert knowledge in conservation science
-
Martin, T. G., Burgman, M. A., Fidler, F., Kuhnert, P. M., Low-Choy, S., McBride, M., & Mengersen, K. (2012). Eliciting expert knowledge in conservation science. Conservation Biology, 26, 29-38. http://dx.doi .org/10.1111/j.1523-1739.2011.01806.x
-
(2012)
Conservation Biology
, vol.26
, pp. 29-38
-
-
Martin, T.G.1
Burgman, M.A.2
Fidler, F.3
Kuhnert, P.M.4
Low-Choy, S.5
McBride, M.6
Mengersen, K.7
-
62
-
-
84887865429
-
Bayesian parametric estimation of stop-signal reaction time distributions
-
Matzke, D., Dolan, C. V., Logan, G. D., Brown, S. D., & Wagenmakers, E. J. (2013). Bayesian parametric estimation of stop-signal reaction time distributions. Journal of Experimental Psychology: General, 142, 1047- 1073. http://dx.doi.org/10.1037/a0030543
-
(2013)
Journal of Experimental Psychology: General
, vol.142
, pp. 1047- 1073
-
-
Matzke, D.1
Dolan, C.V.2
Logan, G.D.3
Brown, S.D.4
Wagenmakers, E.J.5
-
63
-
-
2942651147
-
Sensitivity of Bayes estimators to hyper-parameters with an application to maximum yield from fisheries
-
Millar, R. B. (2004). Sensitivity of Bayes estimators to hyper-parameters with an application to maximum yield from fisheries. Biometrics, 60, 536-542. http://dx.doi.org/10.1111/j.0006-341X.2004.00201.x
-
(2004)
Biometrics
, vol.60
, pp. 536-542
-
-
Millar, R.B.1
-
64
-
-
84928229444
-
Iteration of partially specified target matrices: Applications in exploratory and Bayesian confirmatory factor analysis
-
Moore, T. M., Reise, S. P., Depaoli, S., & Haviland, M. G. (2015). Iteration of partially specified target matrices: Applications in exploratory and Bayesian confirmatory factor analysis. Multivariate Behavioral Research, 50, 149-161. http://dx.doi.org/10.1080/00273171.2014.973990
-
(2015)
Multivariate Behavioral Research
, vol.50
, pp. 149-161
-
-
Moore, T.M.1
Reise, S.P.2
Depaoli, S.3
Haviland, M.G.4
-
65
-
-
84942298440
-
Bayes factor: Computation of Bayes factors for common designs
-
R package version 3.0.2.
-
Morey, R., Rouder, J., & Jamil, T. (2015). Bayes factor: Computation of Bayes factors for common designs. R package version 3.0.2. https://cran .r-project.org/web/packages/BayesFactor/BayesFactor.pdf
-
(2015)
-
-
Morey, R.1
Rouder, J.2
Jamil, T.3
-
66
-
-
84887551125
-
A web-based tool for eliciting probability distributions from experts
-
Morris, D. E., Oakley, J. E., & Crowe, J. A. (2014). A web-based tool for eliciting probability distributions from experts. Environmental Modelling & Software, 52, 1-4. http://dx.doi.org/10.1016/j.envsoft.2013.10 .010
-
(2014)
Environmental Modelling & Software
, vol.52
, pp. 1-4
-
-
Morris, D.E.1
Oakley, J.E.2
Crowe, J.A.3
-
67
-
-
84857411685
-
BIEMS: A Fortran 90 program for calculating Bayes factors for inequality and equality constrained models
-
Mulder, J., Hoijtink, H., & de Leeuw, C. (2012). BIEMS: A Fortran 90 program for calculating Bayes factors for inequality and equality constrained models. Journal of Statistical Software, 46, 1-39. http://dx.doi .org/10.18637/jss.v046.i02
-
(2012)
Journal of Statistical Software
, vol.46
, pp. 1-39
-
-
Mulder, J.1
Hoijtink, H.2
de Leeuw, C.3
-
68
-
-
84873047637
-
Bayesian structural equation modeling: A more flexible representation of substantive theory
-
Muthén, B., & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17, 313-335. http://dx.doi.org/10.1037/a0026802
-
(2012)
Psychological Methods
, vol.17
, pp. 313-335
-
-
Muthén, B.1
Asparouhov, T.2
-
70
-
-
85020265673
-
Early childhood longitudinal study: Kindergarten class of 1998-99: Base year public-use data files user's manual (Tech. Rep. No. NCES 2001-029)
-
Washington, DC: U.S. Government Printing Office.
-
NCES. (2001). Early childhood longitudinal study: Kindergarten class of 1998-99: Base year public-use data files user's manual (Tech. Rep. No. NCES 2001-029). Washington, DC: U.S. Government Printing Office.
-
(2001)
-
-
-
71
-
-
84889367764
-
Bayesian modeling using WinBUGS
-
Hoboken, NJ: Wiley.
-
Ntzoufras, I. (2009). Bayesian modeling using WinBUGS. Hoboken, NJ: Wiley. http://dx.doi.org/10.1002/9780470434567
-
(2009)
-
-
Ntzoufras, I.1
-
72
-
-
85016966585
-
Uncertain judgements: Eliciting experts' probabilities
-
West Sussex, UK: Wiley.
-
O'Hagan, A., Buck, C. E., Daneshkhah, A., Eiser, J. R., Garthwaite, P. H., Jenkinson, D. J., Rakow, T. (2006). Uncertain judgements: Eliciting experts' probabilities. West Sussex, UK: Wiley. http://dx.doi.org/10 .1002/0470033312
-
(2006)
-
-
O'Hagan, A.1
Buck, C.E.2
Daneshkhah, A.3
Eiser, J.R.4
Garthwaite, P.H.5
Jenkinson, D.J.6
Rakow, T.7
-
73
-
-
84864383375
-
Cluster-level covariance analysis for survey data with structured nonresponse
-
Tech. Rep. No. Cambridge, MA: Department of Health Care Policy, Harvard Medical School.
-
O'Malley, A. J., & Zaslavsky, A. M. (2005). Cluster-level covariance analysis for survey data with structured nonresponse. Tech. Rep. No. Cambridge, MA: Department of Health Care Policy, Harvard Medical School.
-
(2005)
-
-
O'Malley, A.J.1
Zaslavsky, A.M.2
-
74
-
-
67650521193
-
JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling
-
Plummer, M. (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Retrieved from http://www-fis.iarc.fr/ ~martyn/software/jags/
-
(2003)
-
-
Plummer, M.1
-
75
-
-
0041745823
-
Subjective and objective Bayesian statistics: Principles, models, and applications (2nd ed.)
-
New York, NY: Wiley
-
Press, S. J. (2003). Subjective and objective Bayesian statistics: Principles, models, and applications (2nd ed.). New York, NY: Wiley.
-
(2003)
-
-
Press, S.J.1
-
76
-
-
0000783674
-
Hypothesis testing and model selection
-
In W. R. Gilks, S. Richardson, & D. J. Spiegelhalter (Eds.), New York, NY: Chapman & Hall.
-
Raftery, A. E. (1996). Hypothesis testing and model selection. In W. R. Gilks, S. Richardson, & D. J. Spiegelhalter (Eds.), Markov chain Monte Carlo in practice (pp. 163-187). New York, NY: Chapman & Hall.
-
(1996)
Markov chain Monte Carlo in practice
, pp. 163-187
-
-
Raftery, A.E.1
-
77
-
-
0000759236
-
How many iterations in the Gibbs sampler
-
Raftery, A. E., & Lewis, S. (1992). How many iterations in the Gibbs sampler. Bayesian statistics, 4, 763-773.
-
(1992)
Bayesian statistics
, vol.4
, pp. 763-773
-
-
Raftery, A.E.1
Lewis, S.2
-
78
-
-
18244378520
-
On Bayesian analysis of mixtures with an unknown number of components
-
Richardson, S., & Green, P. J. (1997). On Bayesian analysis of mixtures with an unknown number of components. Journal of the Royal Statistical Society Series A, 59, 731-792. http://dx.doi.org/10.1111/1467-9868 .00095
-
(1997)
Journal of the Royal Statistical Society Series A
, vol.59
, pp. 731-792
-
-
Richardson, S.1
Green, P.J.2
-
79
-
-
80053386883
-
Incorporation of historical data in the analysis of randomized therapeutic trials
-
Rietbergen, C., Klugkist, I., Janssen, K. J., Moons, K. G., & Hoijtink, H. J. (2011). Incorporation of historical data in the analysis of randomized therapeutic trials. Contemporary Clinical Trials, 32, 848-855. http://dx .doi.org/10.1016/j.cct.2011.06.002
-
(2011)
Contemporary Clinical Trials
, vol.32
, pp. 848-855
-
-
Rietbergen, C.1
Klugkist, I.2
Janssen, K.J.3
Moons, K.G.4
Hoijtink, H.J.5
-
80
-
-
34547596912
-
-
Cary, NC: SAS Institute Inc.
-
SAS Institute Inc. (2012-2013). SAS 9 help and documentation, Cary, NC: SAS Institute Inc.
-
(2012)
SAS 9 help and documentation
-
-
-
81
-
-
85020272452
-
A comparison of Wishart prior specifications for variance-covariance matrices in multilevel autoregressive models
-
(in press). Multivariate Behavioral Research.
-
Schuurman, N. K., Grasman, R. P. P. P., & Hamaker, E. L. (in press). A comparison of Wishart prior specifications for variance-covariance matrices in multilevel autoregressive models. Multivariate Behavioral Research.
-
-
-
Schuurman, N.K.1
Grasman, R.P.P.P.2
Hamaker, E.L.3
-
82
-
-
84865761131
-
Hidden dangers of specifying noninformative priors
-
Seaman, J. W., III, Seaman, J. W., Jr., & Stamey, J. D. (2012). Hidden dangers of specifying noninformative priors. The American Statistician, 66, 77-84. http://dx.doi.org/10.1080/00031305.2012.695938
-
(2012)
The American Statistician
, vol.66
, pp. 77-84
-
-
Seaman, J.W.1
Seaman III, J.W.2
Stamey, J.D.3
-
83
-
-
11844261472
-
Experiences with Markov chain Monte Carlo convergence assessment in two psychometric examples
-
Sinharay, S. (2004). Experiences with Markov chain Monte Carlo convergence assessment in two psychometric examples. Journal of Educational and Behavioral Statistics, 29, 461- 488. http://dx.doi.org/10.3102/ 10769986029004461
-
(2004)
Journal of Educational and Behavioral Statistics
, vol.29
, pp. 461- 488
-
-
Sinharay, S.1
-
84
-
-
84879175911
-
Multilevel and longitudinal modeling using Stata
-
College Station, TX: Stata Press
-
Skrondal, A., & Rabe-Hesketh, S. (2012). Multilevel and longitudinal modeling using Stata. College Station, TX: Stata Press.
-
(2012)
-
-
Skrondal, A.1
Rabe-Hesketh, S.2
-
85
-
-
0003660974
-
Bayesian Output Analysis program (BOA), version 1.1.5.
-
March 23).
-
Smith, B. J. (2005, March 23). Bayesian Output Analysis program (BOA), version 1.1.5. Retrieved from http://www.public-health.uiowa.edu/boa
-
(2005)
-
-
Smith, B.J.1
-
86
-
-
85003226669
-
STAN Modeling Language Users Guide and Reference Manual, Version 2.2
-
Stan Development Team. (2014). STAN Modeling Language Users Guide and Reference Manual, Version 2.2. http://mc-stan.org/citations/
-
(2014)
-
-
-
87
-
-
84899623960
-
Stata 13 base reference manual
-
College Station, TX: Stata Press
-
StataCorp. (2013). Stata 13 base reference manual. College Station, TX: Stata Press.
-
(2013)
-
-
-
88
-
-
40749130885
-
Using response times for item selection in adaptive testing
-
van der Linden, W. J. (2008). Using response times for item selection in adaptive testing. Journal of Educational and Behavioral Statistics, 33, 5-20. http://dx.doi.org/10.3102/1076998607302626
-
(2008)
Journal of Educational and Behavioral Statistics
, vol.33
, pp. 5-20
-
-
van der Linden, W.J.1
-
89
-
-
84977106631
-
Analyzing small data sets using Bayesian estimation: The case of posttraumatic stress symptoms following mechanical ventilation in burn survivors
-
van de Schoot, R., Broere, J. J., Perryck, K. H., Zondervan-Zwijnenburg, M., & van Loey, N. E. (2015). Analyzing small data sets using Bayesian estimation: The case of posttraumatic stress symptoms following mechanical ventilation in burn survivors. European Journal of Psychotraumatology, 6, 25216. http://dx.doi.org/10.3402/ejpt.v6.25216
-
(2015)
European Journal of Psychotraumatology
, vol.6
, pp. 25216
-
-
van de Schoot, R.1
Broere, J.J.2
Perryck, K.H.3
Zondervan-Zwijnenburg, M.4
van Loey, N.E.5
-
91
-
-
79551531781
-
Evaluating expectations about negative emotional states of aggressive boys using Bayesian model selection
-
van de Schoot, R., Hoijtink, H., Mulder, J., Van Aken, M. A., de Castro, B. O., Meeus, W., & Romeijn, J. W. (2011). Evaluating expectations about negative emotional states of aggressive boys using Bayesian model selection. Developmental Psychology, 47, 203-212. http://dx.doi .org/10.1037/a0020957
-
(2011)
Developmental Psychology
, vol.47
, pp. 203-212
-
-
van de Schoot, R.1
Hoijtink, H.2
Mulder, J.3
Van Aken, M.A.4
de Castro, B.O.5
Meeus, W.6
Romeijn, J.W.7
-
92
-
-
84984967085
-
A systematic review of empirical Bayesian applications in psychology
-
(under review).
-
van de Schoot, R., Ryan, O., Winter, S., Zondervan-Zwijenburg, M. A. J., & Depaoli, S. (under review). A systematic review of empirical Bayesian applications in psychology.
-
-
-
van de Schoot, R.1
Ryan, O.2
Winter, S.3
Zondervan-Zwijenburg, M.A.J.4
Depaoli, S.5
-
93
-
-
0042346332
-
Predictors of chronic posttraumatic stress symptoms following burn injury: Results of a longitudinal study
-
van Loey, N. E. E., Maas, C. J. M., Faber, A. W., & Taal, L. A. (2003). Predictors of chronic posttraumatic stress symptoms following burn injury: Results of a longitudinal study. Journal of Traumatic Stress, 16, 361-369. http://dx.doi.org/10.1023/A:1024465902416
-
(2003)
Journal of Traumatic Stress
, vol.16
, pp. 361-369
-
-
van Loey, N.E.E.1
Maas, C.J.M.2
Faber, A.W.3
Taal, L.A.4
-
94
-
-
81855194758
-
Choosing priors for constrained analysis of variance: Methods based on training data
-
Van Wesel, F., Hoijtink, H., & Klugkist, I. (2011). Choosing priors for constrained analysis of variance: Methods based on training data. Scandinavian Journal of Statistics, 38, 666-690. http://dx.doi.org/10.1111/j .1467-9469.2010.00719.x
-
(2011)
Scandinavian Journal of Statistics
, vol.38
, pp. 666-690
-
-
Van Wesel, F.1
Hoijtink, H.2
Klugkist, I.3
-
96
-
-
80051813363
-
Statistical evidence in experimental psychology an empirical comparison using 855 t tests
-
Wetzels, R., Matzke, D., Lee, M. D., Rouder, J. N., Iverson, G. J., & Wagenmakers, E. J. (2011). Statistical evidence in experimental psychology an empirical comparison using 855 t tests. Perspectives on Psychological Science, 6, 291-298. http://dx.doi.org/10.1177/ 1745691611406923
-
(2011)
Perspectives on Psychological Science
, vol.6
, pp. 291-298
-
-
Wetzels, R.1
Matzke, D.2
Lee, M.D.3
Rouder, J.N.4
Iverson, G.J.5
Wagenmakers, E.J.6
-
97
-
-
34347330128
-
Bayesian analysis of longitudinal data using growth curve models
-
Zhang, Z., Hamagami, F., Wang, L., Grimm, K. J., & Nesselroade, J. R. (2007). Bayesian analysis of longitudinal data using growth curve models. International Journal of Behavioral Development, 31, 374-383. http://dx.doi.org/10.1177/0165025407077764
-
(2007)
International Journal of Behavioral Development
, vol.31
, pp. 374-383
-
-
Zhang, Z.1
Hamagami, F.2
Wang, L.3
Grimm, K.J.4
Nesselroade, J.R.5
|