Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure
The paper addresses the issue of identifying the maximum safe dose in the context of noninferiority trials where several doses of toxicological compounds exist. Statistical methodology for identifying the maximum safe dose is available for three-arm noninferiority designs with only one experimental...
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Online Access: | http://dx.doi.org/10.1155/2019/3249097 |
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doaj-b147eb663bc4452fa63b1448d9ece52b2020-11-25T00:40:29ZengHindawi LimitedJournal of Probability and Statistics1687-952X1687-95382019-01-01201910.1155/2019/32490973249097Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence ProcedureMichael J. Adjabui0Nathaniel K. Howard1Mathias Akamba2Department of Mathematics, University for Development Studies, Navrongo, GhanaDepartment of Statistics, University of Cape Coast, Cape Coast, GhanaDepartment of Statistics, University for Development Studies, Navrongo, GhanaThe paper addresses the issue of identifying the maximum safe dose in the context of noninferiority trials where several doses of toxicological compounds exist. Statistical methodology for identifying the maximum safe dose is available for three-arm noninferiority designs with only one experimental drug treatment. Extension of this methodology for several experimental groups exists but with multiplicity adjustment. However, if the experimental or the treatment groups can be ordered a priori according to their treatment effect, then multiplicity adjustment is unneeded. Assuming homogeneity of variances across dose group in normality settings, we employed the generalized Fieller’s confidence interval method in a multiple comparison stepwise procedure by incorporating the partitioning principle in order to control the familywise error rate (FWER). Simulation results revealed that the procedure properly controlled the FWER in strong sense. Also, the power of our procedure increases with increasing sample size and the ratio of mean differences. We illustrate our procedure with mutagenicity dataset from a clinical study.http://dx.doi.org/10.1155/2019/3249097 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Michael J. Adjabui Nathaniel K. Howard Mathias Akamba |
spellingShingle |
Michael J. Adjabui Nathaniel K. Howard Mathias Akamba Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure Journal of Probability and Statistics |
author_facet |
Michael J. Adjabui Nathaniel K. Howard Mathias Akamba |
author_sort |
Michael J. Adjabui |
title |
Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure |
title_short |
Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure |
title_full |
Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure |
title_fullStr |
Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure |
title_full_unstemmed |
Biostatistical Assessment of Mutagenicity Studies: A Stepwise Confidence Procedure |
title_sort |
biostatistical assessment of mutagenicity studies: a stepwise confidence procedure |
publisher |
Hindawi Limited |
series |
Journal of Probability and Statistics |
issn |
1687-952X 1687-9538 |
publishDate |
2019-01-01 |
description |
The paper addresses the issue of identifying the maximum safe dose in the context of noninferiority trials where several doses of toxicological compounds exist. Statistical methodology for identifying the maximum safe dose is available for three-arm noninferiority designs with only one experimental drug treatment. Extension of this methodology for several experimental groups exists but with multiplicity adjustment. However, if the experimental or the treatment groups can be ordered a priori according to their treatment effect, then multiplicity adjustment is unneeded. Assuming homogeneity of variances across dose group in normality settings, we employed the generalized Fieller’s confidence interval method in a multiple comparison stepwise procedure by incorporating the partitioning principle in order to control the familywise error rate (FWER). Simulation results revealed that the procedure properly controlled the FWER in strong sense. Also, the power of our procedure increases with increasing sample size and the ratio of mean differences. We illustrate our procedure with mutagenicity dataset from a clinical study. |
url |
http://dx.doi.org/10.1155/2019/3249097 |
work_keys_str_mv |
AT michaeljadjabui biostatisticalassessmentofmutagenicitystudiesastepwiseconfidenceprocedure AT nathanielkhoward biostatisticalassessmentofmutagenicitystudiesastepwiseconfidenceprocedure AT mathiasakamba biostatisticalassessmentofmutagenicitystudiesastepwiseconfidenceprocedure |
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