13 articles
Articles prepublished February 07, 2012
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Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Preprint Online November 21, 2011
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Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Articles prepublished September 14, 2010
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Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Preprint Online August 05, 2011
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Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Preprint Online July 26, 2011
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Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Preprint Online March 21, 2011
|
|
Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
Preprint Online March 04, 2011
|
|
Blinded Sample Size Reestimation with Negative Binomial Counts in Superiority and Non-inferiority Trials
Special Topic: GMDS 2009
T. Friede (1), H. Schmidli (2)
(1) Abteilung Medizinische Statistik, Universitätsmedizin Göttingen, Göttingen, Germany; (2) Statistical Methodology, Novartis Pharma AG, Basel, Switzerland
Summary
Background: In the planning of clinical trials with count outcomes such as the number of exacerbations in chronic obstructive pulmonary disease (COPD) often considerable uncertainty exists with regard to the overall event rate and the level of overdispersion which are both crucial for sample size calculations. Objectives: To develop a sample size reestimation strategy that maintains the blinding of the trial, controls the type I error rate and is robust against misspecification of the nuisance parameters in the planning phase in that the actual power is close to the target. Methods: The operation characteristics of the developed sample size reestimation procedure are investigated in a Monte Carlo simulation study. Results: Estimators of the overall event rate and the overdispersion parameter that do not require unblinding can be used to effectively adjust the sample size without inflating the type I error rate while providing power values close to the target. Conclusions: If only little information is available regarding the size of the overall event rate and the overdispersion parameter in the design phase of a trial, we recommend the use of a design with sample size reestimation as the one suggested here. Trials in COPD are expected to benefit from the proposed sample size reestimation strategy.
Keywords
Clinical Trial, Sample Size, COPD, chronic obstructive pulmonary disease, Internal pilot study
DOI
http://dx.doi.org/10.3414/ME09-02-0060You may also be interested in...
| 1. | ||
R. Grütter (1) , W. Fierz (2) Methods of Information in Medicine 1999 38 3: 154-157 | ||
| 2. | ||
J. Wöhrle1*, T. Nusser1*, B. J. Krause4*, M. Kochs1, T. Habig1, F. M. Mottaghy3, H. A. Kestler2, V. Hombach1, S. N. Reske3 Nuklearmedizin 2007 46 5: 185-191 http://dx.doi.org/10.1160/nukmed-0084 | ||
| 3. | ||
C. Tschöpe1, M. Leschke2 Die Medizinische Welt 2007 58 9: 403-410 | ||
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