The Experts below are selected from a list of 16581 Experts worldwide ranked by ideXlab platform
Eshetu G Atenafu - One of the best experts on this subject based on the ideXlab platform.
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the special case of the 2 2 table asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on gee
Journal of Clinical Epidemiology, 2015Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
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The special case of the 2 × 2 table: asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on GEE
Journal of clinical epidemiology, 2014Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
Cornelia M Borkhoff - One of the best experts on this subject based on the ideXlab platform.
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the special case of the 2 2 table asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on gee
Journal of Clinical Epidemiology, 2015Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
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The special case of the 2 × 2 table: asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on GEE
Journal of clinical epidemiology, 2014Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
John M. Lachin - One of the best experts on this subject based on the ideXlab platform.
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POWER AND SAMPLE SIZE EVALUATION FOR THE McNemar Test WITH APPLICATION TO MATCHED CASE-CONTROL STUDIES
Statistics in Medicine, 1992Co-Authors: John M. LachinAbstract:Various expressions have appeared for sample size calculation based on the power function of McNemar's Test for paired or matched proportions, especially with reference to a matched case-control study. These differ principally with respect to the expression for the variance of the statistic under the alternative hypothesis. In addition to the conditional power function, I identify and compare four distinct unconditional expressions. I show that the unconditional calculation of Schlesselman for the matched case-control study can be expressed as a first-order unconditional calculation as described by Miettinen. Corrections to Schlesselman's unconditional expression presented by Fleiss and Levin and by Dupont, which use different models to describe exposure association among matched cases and controls, are also equivalent to a first-order unconditional calculation. I present a simplification of these corrections that directly provides the underlying table of cell probabilities, from which one can perform any of the alternative sample size calculations. Also, I compare the four unconditional sample size expressions relative to the exact power function. The conclusion is that Miettinen's first-order expression tends to underestimate sample size, while his second-order expression is usually fairly accurate, though possibly slightly anti-conservative. A multinomial-based expression presented by Connor, among others, is also fairly accurate and is usually slightly conservative. Finally, a local unconditional expression of Mitra, among others, tends to be excessively conservative.
Patrick R Johnston - One of the best experts on this subject based on the ideXlab platform.
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the special case of the 2 2 table asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on gee
Journal of Clinical Epidemiology, 2015Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
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The special case of the 2 × 2 table: asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on GEE
Journal of clinical epidemiology, 2014Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
Derek Stephens - One of the best experts on this subject based on the ideXlab platform.
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the special case of the 2 2 table asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on gee
Journal of Clinical Epidemiology, 2015Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
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The special case of the 2 × 2 table: asymptotic unconditional McNemar Test can be used to estimate sample size even for analysis based on GEE
Journal of clinical epidemiology, 2014Co-Authors: Cornelia M Borkhoff, Patrick R Johnston, Derek Stephens, Eshetu G AtenafuAbstract:Abstract Objectives Aligning the method used to estimate sample size with the planned analytic method ensures the sample size needed to achieve the planned power. When using generalized estimating equations (GEE) to analyze a paired binary primary outcome with no covariates, many use an exact McNemar Test to calculate sample size. We reviewed the approaches to sample size estimation for paired binary data and compared the sample size estimates on the same numerical examples. Study Design and Setting We used the hypothesized sample proportions for the 2 × 2 table to calculate the correlation between the marginal proportions to estimate sample size based on GEE. We solved the inside proportions based on the correlation and the marginal proportions to estimate sample size based on exact McNemar, asymptotic unconditional McNemar, and asymptotic conditional McNemar. Results The asymptotic unconditional McNemar Test is a good approximation of GEE method by Pan. The exact McNemar is too conservative and yields unnecessarily large sample size estimates than all other methods. Conclusion In the special case of a 2 × 2 table, even when a GEE approach to binary logistic regression is the planned analytic method, the asymptotic unconditional McNemar Test can be used to estimate sample size. We do not recommend using an exact McNemar Test.
