Simulation program for power and sample size determination in logistic analysis of single nucleotide polymorphisms when the response variable is subject to misclassification
Abstract The main objective of this study was to develop a simulation program to determine the sample size for a clinical study to confirm a genetic-disease association observed in a retrospective exploratory study. The effect of misclassification of a binary response variable on the power is also i...
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| Veröffentlicht in: | Computer methods and programs in biomedicine 2009-10, Vol.96 (1), p.42-48 |
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| container_title | Computer methods and programs in biomedicine |
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| creator | Yamada, Tomomi Kinukawa, Naoko Nakamura, Tsuyoshi Nose, Yoshiaki |
| description | Abstract The main objective of this study was to develop a simulation program to determine the sample size for a clinical study to confirm a genetic-disease association observed in a retrospective exploratory study. The effect of misclassification of a binary response variable on the power is also investigated. A general expression for the magnitude of the decrease in statistical power due to misclassification is obtained based on the Pitman asymptotic relative efficiency. The simulation program presents an estimate of the exact power when misclassification exists. Running the program several times under different settings of parameters, it revealed that the effect of even low misclassification rates is serious. Response misclassification should be taken into consideration when determining the sample size. The program can be used on the Internet. |
| doi_str_mv | 10.1016/j.cmpb.2009.03.007 |
| format | Article |
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The program can be used on the Internet.</description><subject>Asymptotic relative efficiency</subject><subject>Cohort Studies</subject><subject>Genetic-disease association</subject><subject>Genotype</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Logistic Models</subject><subject>Logistic regression</subject><subject>Misclassification</subject><subject>Other</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Sample Size</subject><subject>SNPs</subject><issn>0169-2607</issn><issn>1872-7565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFks2O0zAUhSMEYsrAC7BAXrFruLbrpJEQEhrxJ43EYmBtOc516-LEwTeZUXkn3hFnWgmJBbPy5jvnWueconjJoeTAqzeH0vZjWwqApgRZAtSPihXf1mJdq0o9LlYZataigvqieEZ0AAChVPW0uODNBiRv5Kr4feP7OZjJx4GNKe6S6ZmLiY3xDhMzQ8fI9GNARv4Xsg4nTL0fTrwfWIg7T5O3mTThSJ5YdBkddlkxzDZgnHyH2S0c-5jGvaee2N0eBzbtkSWkMQ6E7NYkb9qsyQY0twe0E5si6z3ZYIi88_b-5PPiiTOB8MX5vSy-f_zw7erz-vrrpy9X76_XdlPzae2M4widlQIb51qhWlBgjGu7Wki3VY4DCuSWC2HBoVHIlURlcVPBVlRSXhavT745kp8z0qSXr2AIZsA4k65qJUDJzYOg3GyhqnPSD4EC6m1d358WJ9CmSJTQ6TH53qSj5qCX2vVBL7XrpXYNUufas-jV2X1ue-z-Ss49Z-DtCcCc2q3HpMl6HCx2PuWwdRf9__3f_SO3wQ-5lPADj0iHOKfcP2muSWjQN8vwlt1BkzfXVCD_APt72Ro</recordid><startdate>20091001</startdate><enddate>20091001</enddate><creator>Yamada, Tomomi</creator><creator>Kinukawa, Naoko</creator><creator>Nakamura, Tsuyoshi</creator><creator>Nose, Yoshiaki</creator><general>Elsevier Ireland Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>7SC</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope></search><sort><creationdate>20091001</creationdate><title>Simulation program for power and sample size determination in logistic analysis of single nucleotide polymorphisms when the response variable is subject to misclassification</title><author>Yamada, Tomomi ; 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The effect of misclassification of a binary response variable on the power is also investigated. A general expression for the magnitude of the decrease in statistical power due to misclassification is obtained based on the Pitman asymptotic relative efficiency. The simulation program presents an estimate of the exact power when misclassification exists. Running the program several times under different settings of parameters, it revealed that the effect of even low misclassification rates is serious. Response misclassification should be taken into consideration when determining the sample size. The program can be used on the Internet.</abstract><cop>Ireland</cop><pub>Elsevier Ireland Ltd</pub><pmid>19403193</pmid><doi>10.1016/j.cmpb.2009.03.007</doi><tpages>7</tpages></addata></record> |
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| ispartof | Computer methods and programs in biomedicine, 2009-10, Vol.96 (1), p.42-48 |
| issn | 0169-2607 1872-7565 |
| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Asymptotic relative efficiency Cohort Studies Genetic-disease association Genotype Humans Internal Medicine Logistic Models Logistic regression Misclassification Other Polymorphism, Single Nucleotide Sample Size SNPs |
| title | Simulation program for power and sample size determination in logistic analysis of single nucleotide polymorphisms when the response variable is subject to misclassification |
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