Correction to "Doubly‐robust dynamic treatment regimen estimation via weighted least squares," by Michael P. Wallace and Erica E. M. Moodie; 71 (3), 636–644, September 2015.
- Published in:
- 2020
- Publication type:
- Correction Notice
Works matching IS 0006341X AND DT 2020 AND VI 76 AND IP 2
Results: 37
1
2
Discussion of "Assessing the goodness‐of‐fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test," by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 569, doi. 10.1111/biom.13255
- By:
- Publication type:
- Article
3
Bayesian statistical methods.
- Published in:
- 2020
- By:
- Publication type:
- Book Review
4
Discussion on "Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test" by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 561, doi. 10.1111/biom.13257
- By:
- Publication type:
- Article
5
Discussion on "Predictively consistent prior effective sample sizes," by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 599, doi. 10.1111/biom.13254
- By:
- Publication type:
- Article
6
Discussion on "Predictively Consistent Prior Effective Sample Sizes" by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 588, doi. 10.1111/biom.13253
- By:
- Publication type:
- Article
7
Predictively consistent prior effective sample sizes.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 578, doi. 10.1111/biom.13252
- By:
- Publication type:
- Article
8
Discussion on "Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test" by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 564, doi. 10.1111/biom.13251
- By:
- Publication type:
- Article
9
Rejoinder to "Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test".
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 575, doi. 10.1111/biom.13250
- By:
- Publication type:
- Article
10
Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 549, doi. 10.1111/biom.13249
- By:
- Publication type:
- Article
11
Discussion on "Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test" by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 572, doi. 10.1111/biom.13248
- By:
- Publication type:
- Article
12
Discussion on "Predictively consistent prior effective sample sizes," by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 591, doi. 10.1111/biom.13247
- By:
- Publication type:
- Article
13
Discussion on "Predictively consistent prior effective sample sizes," by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 595, doi. 10.1111/biom.13246
- By:
- Publication type:
- Article
14
Rejoinder to "Predictively consistent prior effective sample sizes," by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 602, doi. 10.1111/biom.13245
- By:
- Publication type:
- Article
15
Inference in MCMC step selection models.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 438, doi. 10.1111/biom.13170
- By:
- Publication type:
- Article
16
Approximation of bias and mean‐squared error in two‐sample Mendelian randomization analyses.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 369, doi. 10.1111/biom.13169
- By:
- Publication type:
- Article
17
The profile inter‐unit reliability.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 654, doi. 10.1111/biom.13167
- By:
- Publication type:
- Article
18
On Mendelian randomization analysis of case‐control study.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 380, doi. 10.1111/biom.13166
- By:
- Publication type:
- Article
19
Gene‐based association analysis for bivariate time‐to‐event data through functional regression with copula models.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 619, doi. 10.1111/biom.13165
- By:
- Publication type:
- Article
20
Bayesian design of biosimilars clinical programs involving multiple therapeutic indications.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 630, doi. 10.1111/biom.13163
- By:
- Publication type:
- Article
21
Inverse probability weighting methods for Cox regression with right‐truncated data.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 484, doi. 10.1111/biom.13162
- By:
- Publication type:
- Article
22
Designing precision medicine trials to yield a greater population impact.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 643, doi. 10.1111/biom.13161
- By:
- Publication type:
- Article
23
Cox regression with survival‐time‐dependent missing covariate values.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 460, doi. 10.1111/biom.13155
- By:
- Publication type:
- Article
24
Data reduction prior to inference: Are there consequences of comparing groups using a t‐test based on principal component scores?
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 508, doi. 10.1111/biom.13159
- By:
- Publication type:
- Article
25
Adjusting for time‐varying confounders in survival analysis using structural nested cumulative survival time models.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 472, doi. 10.1111/biom.13158
- By:
- Publication type:
- Article
26
Analysis of secondary phenotypes in multigroup association studies.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 606, doi. 10.1111/biom.13157
- By:
- Publication type:
- Article
27
Simultaneous confidence corridors for mean functions in functional data analysis of imaging data.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 427, doi. 10.1111/biom.13156
- By:
- Publication type:
- Article
28
Sequential adaptive variables and subject selection for GEE methods.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 496, doi. 10.1111/biom.13160
- By:
- Publication type:
- Article
29
An adaptive independence test for microbiome community data.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 414, doi. 10.1111/biom.13154
- By:
- Publication type:
- Article
30
Penalized survival models for the analysis of alternating recurrent event data.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 448, doi. 10.1111/biom.13153
- By:
- Publication type:
- Article
31
Bias correction of bounded location error in binary data.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 530, doi. 10.1111/biom.13152
- By:
- Publication type:
- Article
32
A spatial open‐population capture‐recapture model.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 392, doi. 10.1111/biom.13150
- By:
- Publication type:
- Article
33
Equivalence of regression curves sharing common parameters.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 518, doi. 10.1111/biom.13149
- By:
- Publication type:
- Article
34
Sharp bounds on the relative treatment effect for ordinal outcomes.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 664, doi. 10.1111/biom.13148
- By:
- Publication type:
- Article
35
Multinomial N‐mixture models for removal sampling.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 540, doi. 10.1111/biom.13147
- By:
- Publication type:
- Article
36
A heterogeneity measure for cluster identification with application to disease mapping.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 403, doi. 10.1111/biom.13145
- By:
- Publication type:
- Article
37
Issue Information.
- Published in:
- Biometrics, 2020, v. 76, n. 2, p. 365, doi. 10.1111/biom.13089
- Publication type:
- Article