Statistical Methods. In the database congenital malformations are classified through a standard coding system by organ system into specific categories or into non-specific categories if no details are known. Eight different organ systems are distinguished for which there are 51 specified and 20 unspecified categories of congenital malformations. Logistic regression models were used to study the relationship between maternal ethnicity and congenital malformations. The overall relationship between ethnic group and the total prevalence of congenital malformations, the total prevalence within the eight organ systems and the prevalence of some specific congenital malformations was determined with the Likelihood Ratio Test (LRT). If this test was significant it showed the existence of an overall relationship between ethnicity and congenital malformations. Thereafter, the individual significance of the calculated odds ratios (ORs) expressing the observed risk differences in prevalence between the different ethnic groups and the Dutch group, used as reference group, was studied. Because maternal age is related to the ethnic group and to the occurrence of certain congenital malformations, we calculated the ORs both unadjusted and adjusted for the age of the mother. Because the prevalence of some malformations was low, even in this 5-year birth cohort, not all could be tested. We decided that the predicted number of malformations had to be at least 5 in each ethnic group to perform a worthwhile and clinically significant test. Therefore, from the 51 specific malformations registered in the linked national database only the following 15 were analysed for possible differences between ethnic groups: neural tube defects (NTD); congenital malformations of the ears; ventricular septal defect; single umbilical artery; cleft lip with/without cleft palate; cleft palate without cleft lip; intestinal/anorectal atresia; hypospadias and/or epispadias; undescended testes; polydactyly; syndactyly; deformities of the foot without NTD; Down’s syndrome; other chromosomal malformations; and multiple malformations. Many comparisons were performed to test for a possible ethnic difference in prevalence of any congenital malformations. To avoid chance findings resulting from to multiple testing we applied a Bonferroni correction in which the usual critical value of 0.05 is adapted to a lower one depending on the number of tests performed. For example, to determine in which of the ethnic groups a possible diff...
Statistical Methods. Two statistical methods were used to perform the GWAS, namely weighted single-step GBLUP (WssGBLUP; Xxxx et al. 2012) and XxxxxX (Xxxxxx et al. 2011). The model adopted for WssGBLUP was: y=1µ+Zaa+e, where y is the vector of phenotypes, µ is the overall mean, a is the vector of additive genetic effects, 1 is a vector of ones, Za is an incidence matrix relating the phenotypes to a, and e is the vector of residuals. The covariance between a and e was assumed to be zero and their variances were considered to be Hσ 2 and Iσ 2, respectively, where σ 2 a e a e and σ 2 are the direct additive and residual variance, respectively, H is the matrix which combines pedigree and genomic information (Xxxxxxx et al. 2010), and I is an identity matrix. The SNP effects (û) were calculated as in Stranden & Xxxxxxx (2009): û=DP’[PDP’]-1ag, where D is a diagonal matrix that contains the weights for the SNPs, P is a matrix relating genotypes of each locus (coded as 0, 1 or 2 according to the number of copies of allele B) and ag is a vector with the estimated breeding values of genotyped animals. D, â and û were iteratively recomputed over three iterations. In the first iteration (w1), the diagonal elements of D (di) were assumed to be 1 (i.e., the same weight for all markers). For the subsequent iterations (w2 and w3), di was calculated as: di=ûi2pi(1-pi), where ûi is the allele substitution effect of the ith marker, estimated from the previous iteration, and pi is the allele frequency of the second allele of the ith marker. The WssGBLUP was adopted using two sets of data, one considering all available phenotypic information (SI; n=45,000) and another considering phenotypes just from genotyped animals (SII; n=2,000). The three different weights for the SNPs (w1 to w3) and the two sets of data (SI and SII) resulted in six different solutions for the SNP effects obtained under the WssGBLUP method. BayesC was applied under the model:
Statistical Methods. A randomization analysis was conducted to check the comparability of the different conditions at baseline. This was done by chi-square statistics for categorical and dichotomous variables, while t-tests were used for continuous variables. An attrition analysis was conducted to see whether there were differences in baseline scores between the participants who remained in the study and those who withdrew at post-test. This was done by analyses of variance and chi-square. Finally, to check the effectiveness of the tailored letters, logistic regression analyses were conducted with benzodiazepine cessation at post-test as the dependent variable (‘0’- did not quit and ‘1’ – did quit) and condition as the independent variable. All comparisons between the intervention conditions were adjusted for age, gender and benzodiazepine dose (in diazepam equivalents). Results
Statistical Methods. Comparisons between treatments will be assessed using a *** with factors of *** and ***, and with ***. A step down multiple comparison procedure will be utilized to protect overall ***. For the first level of testing, the response to the *** will be compared to ***, and to ***. If each of these *** comparisons is significant at the *** for both of the co-primary endpoints, then this combination will be considered to have met requirements, and testing will continue to the second level, which will evaluate the *** compared to *** and ***. If all comparisons at the second level are met at the ***, differences in treatment effect between the *** and the ***, the ***, and the *** will be presented using ***. *** INDICATES MATERIAL THAT WAS OMITTED AND FOR WHICH CONFIDENTIAL TREATMENT WAS REQUESTED. ALL SUCH OMITTED MATERIAL WAS FILED SEPARATELY WITH THE SECURITIES AND EXCHANGE COMMISSION PURSUANT TO RULE 24b-2 PROMULGATED UNDER THE SECURITIES EXCHANGE ACT OF 1934, AS AMENDED. TABLE OF CONTENTS INTERNAL PROTOCOL APPROVAL 2 PRINCIPAL INVESTIGATOR SIGNATURE 2 PROTOCOL SYNOPSIS 3 TABLE OF CONTENTS 5 1. INTRODUCTION 11 1.1. Background 11 1.2. Rationale 12 2. TRIAL OBJECTIVES 12
Statistical Methods. All subjects who received any amount of treatment will be included in the report. The primary outcome measure is the subject’s overall tolerability of the adjuvant combination treatment as compared to the standard of care post fractional RF treatment. The self-assessment will be based on a 5-point Likert scale - Subject Tolerability Scale (Appendix A). Summary statistics will be generated for subject tolerability immediately after treatment, 24 hours and 72 hours following treatment as per the terms: Very tolerable, tolerable, having no opinion, intolerable and very intolerable. The secondary outcomes measures are the subject’s degree of discomfort and/or pain as measured by the visual analogue scale (VAS), the incidence of spontaneous adverse events (AEs) and the investigator’s assessment of improvement using the Xxxxxxxxxxx Wrinkle and Elastosis Scale scores before and after treatment as well as Global Aesthetic Improvement Scale (GAIS) for each subject. VAS scores from the treated group will be compared with the VAS scores of the standard of care group. The investigator’s assessment of improvement using the Xxxxxxxxxxx Wrinkle and Elastosis Scale from the treatment group will be compared with that of the standard of care group. The GAIS scores for both groups will also be compared. Summary statistics will also be generated for all treatment emergent adverse events (TEAs). The following types will be reported: • Overall TEAEs • Severe TEAEs • TEAEs related to treatment • Serious Adverse Events (SAEs) • SAEs related to treatment • TEAEs leading to treatment discontinuation
Statistical Methods. Pharmacodynamics: The pharmacodynamic analysis will be based on all subjects who have evaluable change in ***** For each concentration-time point, a change from baseline value (in percent) will be calculated as follows: ***** The individual percent change from baseline values of ***** will be evaluated using model-independent methods as implemented in *****. Data permitting, the following pharmacodynamic parameters will be determined: ***** The rational for deriving partial average changes from baseline for select time intervals is the *****: a) ***** concentrations appears to be correlated to the baseline ***** concentration which could affect interpretation of the changes in ***** in the later portion of the concentration-time profile b) Intersubject variability due to the severity of the disease state is likely to affect the rate of ***** which could affect interpretation of the changes in ***** in the later portion of the concentration-time profile c) The potential of differences in ***** may affect the ***** Descriptive statistics (N, mean, standard deviation, CV, median, minimum, and maximum) will be used to summarize the percent change from baseline concentration data at each planned sampling time point for each treatment. Change from baseline pharmacodynamic parameters will also be summarized by treatment using descriptive statistics. Similarity in ***** will be evaluated for the percent change from baseline pharmacodynamic parameters for ***** (prepared from *****) relative to ***** (prepared from *****)] with an analysis of their pharmacodynamic parameters. An ***** with terms for subject, period, sequence, and treatment will be performed for the parameters ***** above. One-sided 95% confidence intervals (CI) for the test/reference mean ratios will be estimated from the ***** to assess ***** of the test treatments using *****. The test treatment will be compared with the reference treatment and ***** will be declared if the 95% confidence limit for the test to reference ratios are greater than ***** for all of the identified parameters. Similarity in ***** be evaluated for the percent change from baseline pharmacodynamic parameters for ***** (prepared from *****) relative to both ***** (prepared from *****) and ***** (prepared from *****)] using the same ***** model described above. One-sided 95% confidence intervals (CIs) for the test/reference mean ratios will be estimated from the ***** to assess ***** of the test treatments using *****. Treat...
Statistical Methods. The reporting on statistical methods is a core information for reproducing the results of a study or for replicating a study with new participants. A common feature of observational studies is that their results are especially prone to bias and that any measures taken to counteract potential bias need to be reported in order to be able to judge the validity of the study. The specific questions for this dimension are: In the results or discussion section:
Statistical Methods. 12.1.1 Comparisons of Interest [***]
Statistical Methods. All subjects who are randomized, take one or more doses of test material and have at least one post treatment efficacy measurement will be included in the analysis. Comparisons between treatments will be assessed using an *** with factors of ***, *** and *** and with *** for percent weight loss, and *** for percentage of subjects with at least 5% weight loss. A step-down multiple comparison procedure will be used to compare each dose group with ***. That is, comparison with *** will start at the ***. If the statistical test is significant at *** for *** INDICATES MATERIAL THAT WAS OMITTED AND FOR WHICH CONFIDENTIAL TREATMENT WAS REQUESTED. ALL SUCH OMITTED MATERIAL WAS FILED SEPARATELY WITH THE SECURITIES AND EXCHANGE COMMISSION PURSUANT TO RULE 24b-2 PROMULGATED UNDER THE SECURITIES EXCHANGE ACT OF 1934, AS AMENDED. both co-primary endpoints, then the test will proceed to the *** also at the ***. If the statistical comparison is not significant at the ***, then the statistical test will be stopped and the *** will not be tested. If both dose groups are significantly better than ***, then the two active dose groups will be compared. A *** of difference in response rate between treatment groups will be derived. The *** for subjects who discontinue treatment prior to completion of the study, ***. *** INDICATES MATERIAL THAT WAS OMITTED AND FOR WHICH CONFIDENTIAL TREATMENT WAS REQUESTED. ALL SUCH OMITTED MATERIAL WAS FILED SEPARATELY WITH THE SECURITIES AND EXCHANGE COMMISSION PURSUANT TO RULE 24b-2 PROMULGATED UNDER THE SECURITIES EXCHANGE ACT OF 1934, AS AMENDED. TABLE OF CONTENTS INTERNAL PROTOCOL APPROVAL 2 PRINCIPAL INVESTIGATOR SIGNATURE 3 PROTOCOL SYNOPSIS 4
Statistical Methods. All CITs were built within R Studio (53) using the party package (43, 54) within the R programming language (55). As a result of having a large number of significance tests for multiple independent variables, a Bonferroni correction was implemented to reduce the subsequent increased possibility of type I error (56, 57). After this correction was applied to significance tests, a significance level (α) of
