Identifying Minimum Effective Dose Under Heteroscedasticity

We propose a stepwise confidence procedure for identifying minimum effective dose (MED) without multiplicity adjustment.Stepwise procedures strongly control the familywise error rate (FWER) which is a critical requirement for statistical methodologies in identification of MED. The partitioning principle is invoked to validate the control of the FWER. Our simulation study indicates that the FWER was properly controlled in the case with balanced design but failed in some cases of sample sizes for situations of unbalanced design. In addition, the power of the procedure increases with increasing mean of ratio differences and the sample sizes.

Which of the favorite optimal cut-off determination methods is preferable for the ordinal response data? A simulation study

The aim of this study is to investigate the performance of the optimal cut-off methods, which are generally used for the diagnostic tests with the continuous response, for the tests with the ordinal response. Diagnostic accuracy studies examine the ability of a diagnostic test to discriminate between the patients with and without the condition. For diagnostic tests with a continuous response, it is important in practice to calculate the optimal cut-off point that can differentiate patients and healthy individuals. There are many methods proposed in the literature to obtain the optimal cut-point value for continuous test results. The Youden index, the point closest-to-(0, 1) corner in the ROC plane approach, the concordance probability, and the minimum P-value approach are commonly used methods to determine optimal-cut-point. But the researches examining the performance of these methods in the setting of the ordinal response tests are lacking in the literature. So, we compared the mentioned optimal cut-off methods for the ordinal response data by the way of simulation design by considering the sample size and the balance of groups as simulation conditions. The sample sizes of the diseased and non-diseased group were set (50, 50), (100, 100), and (200, 200) for balanced design and (50, 100), (50, 150) and (50, 200) for unbalanced design. For each scenario, 1000 repeats were generated. The differences between the estimated and the true cut-off points (biases) were calculated. All these methods overestimated the true cut-off point, but the median biases of the methods were varying. For the unbalanced design, the same result was relevant but for the balanced design, the minimum P-value approach had a median bias as 0 while others have 1.

Estimation of genetic parameters for litter traits in grasscutters (Thryonomys swinderianus)

A study was conducted to estimate genetic parameters for litter traits in grasscutters. Data were obtained using 209 progenies from an unbalanced design of 18 does nested under six bucks. Heritability values of 0.56 ± 0.21 and 0.22 ± 0.22 were obtained for litter weight at birth from dam component and both sire and dam components, respectively. For litter weight at weaning, the heritability estimate was 0.66 ± 0.22 using the dam component of variance. Genetic correlation between litter weight at birth and litter weight at weaning was 0.59 revealing a positive relationship between both traits.

Fire Cause: Overheated Electrical Outlet Boxes?

When installed with the long axis vertically two receptacle outlet boxes may have approximately six times the heating per inch width as supply conductors per inch length. Unbalanced design with fire danger under overload or fault exists as regards internal box heating and temperature rise. The required National Electrical Code six inch free conductor length is a contributing cause. This also applies to fires from overhead fixture boxes. In time pyrolysis phenomena can cause fires at such boxes. Recommendations are made as to what should be done to alleviate this unbalanced design and dangerous situation.