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AOA, I think the objectives and Statistical analysis are not matched. The best analysis for first objective was to fine sensitivity and specificity. OR are also good to report but not for first objective.. Thanks a lot Asif Hanif Biostatistician and Research Methodologist.
Posted by: biostat on Sep 2009

Hi writer, well done clinically, but some weak areas statistically. Your first objective could only be proved by multiple regression model or logistic model. ANOVA can also be used. when you use OR you must write confidence interval for its statistical significance. Pearson correlation can be used to determine the relationship between variables BMI. BF, WC. My brother (ID BIOSTATS) suggested sensitvity and speificity which is only in the case of Diagnostic and screening procedures.
Posted by: ibrahim_ap on Sep 2009

The prevalence of obesity is rising in our society especially children and young adults of middle and upper social class. girls are more often affected with many social and psychological impacts.
Posted by: bvhospital on Nov 2009

Several issues, first, there is no gold-standard test in this study to determine body fat. While authors write that measuring triceps fold thickness tells about percentage body fat, it is not true. These are easy to use instruments, but have lot of measurement error. Thus, it is not possible to say that one instrument is better than the other unless we exactly measure body fat content. Authors may have tried to use regression calibration or similar other methods to correct for measurement error. Second, the least one need to report for the first objective is sensitivity and specificity of the tests against 'standard test' (which in this case could be a regression calibration corrected instrument of measurement). Better would be to actually have ROC curve and give c-statistic. However appropriate reporting would have been to do report misclassification rates. Third, depending upon whether the outcome is continuous (BMI, skin-fold thickness, WC) or dichotomous (obesity) multiple linear regression or logistic regression can be used. Regardless whichever test is used, 95%CI should be reported.
Posted by: rqayyum on Dec 2009

Several issues, first, there is no gold-standard test in this study to determine body fat. While authors write that measuring triceps fold thickness tells about percentage body fat, it is not true. These are easy to use instruments, but have lot of measurement error. Thus, it is not possible to say that one instrument is better than the other unless we exactly measure body fat content. Authors may have tried to use regression calibration or similar other methods to correct for measurement error. Second, the least one need to report for the first objective is sensitivity and specificity of the tests against 'standard test' (which in this case could be a regression calibration corrected instrument of measurement). Better would be to actually have ROC curve and give c-statistic. However appropriate reporting would have been to do report misclassification rates. Third, depending upon whether the outcome is continuous (BMI, skin-fold thickness, WC) or dichotomous (obesity) multiple linear regression or logistic regression can be used. Regardless whichever test is used, 95%CI should be reported.
Posted by: rqayyum on Dec 2009

Several issues, first, there is no gold-standard test in this study to determine body fat. While authors write that measuring triceps fold thickness tells about percentage body fat, it is not true. These are easy to use instruments, but have lot of measurement error. Thus, it is not possible to say that one instrument is better than the other unless we exactly measure body fat content. Authors may have tried to use regression calibration or similar other methods to correct for measurement error.
Posted by: rqayyum on Dec 2009

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