Statistical Methods Sample Clauses

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 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. 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. 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).

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 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, ***. INTERNAL PROTOCOL APPROVAL 2 PRINCIPAL INVESTIGATOR SIGNATURE 3 PROTOCOL SYNOPSIS 4

Statistical Methods. 12.1.1 Comparisons of Interest [***]

Statistical Methods. Statistical significance was set at P < .05. Data were analyzed by the Xxxx-Xxxxxxx rank sum test and Xxxxxx exact test, where appropriate. Computations were performed with the SigmaStat for Windows software (V.2.03, SPSS, Chicago, IL). The median age of the patients was 53.5 years (range, 27- 89 years). Seventy-two carcinomas were of infiltrating ductal type, 11 were infiltrating lobular, 9 were invasive cancers with ductal and lobular features, 3 were mucinous (colloid) carci- Downloaded from xxxxx://xxxxxxxx.xxx.xxx/ajcp/article/113/2/251/1757825 by guest on 27 September 2020 ❚Image 2❚ Scoring system for HER-2/neu protein immunohis- tochemistry used at PhenoPath Laboratories. A, Completely negative, 0 (original magnification ×400). B, Faint membra- nous positivity, 1+ (original magnification ×400). C, Moderate membranous positivity, 2+ (original magnification ×400). D, Strong, circumferential membranous positivity, 3+ (original magnification ×400). E, Extremely strong, circumferential membranous positivity, 4+ (original magnification ×400). Downloaded from xxxxx://xxxxxxxx.xxx.xxx/ajcp/article/113/2/251/1757825 by guest on 27 September 2020 nomas, 3 were tubular carcinomas, 1 was an invasive micropapillary carcinoma, and 1 was a metaplastic carcinoma. The median size of the tumors was 15 mm (range, 6-102 mm). Histologic grading was performed using the Xxxxxx and Xxxxx modification of the Xxxxx-Xxxxxxxxxx grading system.67 Twenty-seven carcinomas were grade 1, 37 were grade 2, and 35 were grade 3. The metaplastic carcinoma was not graded, since there are no universally accepted criteria for the grading of such lesions. Forty-two of the cases were axillary lymph node–negative and 33 were node-positive. Axillary lymph node status was not available for 25 patients. Seventy-eight cases were estrogen receptor positive and 20 were negative. The estrogen receptor status was not determined in 2 cases. At BIDMC, 97 of the 100 cases were evaluable for HER-2/neu, with 23 (24%) of these 97 cases interpreted as positive. All 3 unevaluable cases had no invasive carcinoma present on the immunostained slides. At PPL, 96 of the 100 cases were evaluable for HER-2/neu, with 22 (23%) of these 96 cases interpreted as positive. All 4 unevaluable cases had tumor cell membrane staining of 1+ or 2+ but no normal breast ducts or lobules on the slide. A total of 93 cases were evaluable in both laboratories. There was complete concordance with regard to categorization of HER-2/neu ...

Statistical Methods. The physical addresses of all 242 Title X publicly-funded family planning clinic sites in Georgia for the year 2006 were geocoded using ArcGis (ArcMapVersion 10). Next, we used the American Community Survey data files to characterize each zip code in Georgia with regard to key population-level characteristics (e.g., proportion of households below the federal poverty line, and with characteristics such as race/ethnicity and age). The NSFG race- and age-specific estimates were used to estimate the proportion of the base population “at risk” of unintended pregnancy in each census tract and HUD tract-zip code crosswalk file were used to aggregate the population at risk in each zip code area. We then utilized Georgia’s pregnancy termination file to calculate the number pregnancy terminations occurring for each of the state’s zip codes for 2006. For each ZCTA, an abortion rate was calculated based upon the total number of terminated pregnancies over the total number of women of reproductive age (15-44 years) at risk of unintended pregnancy residing in the geographic area. The covariates were variables that were both included in our dataset and in past studies shown to be associated with unintended pregnancies. These variables included the woman’s age category (15-17, 18-19, 20-24, 25-29, 30- 34, and 35-44), ethnicity and race (non-Hispanic White, non-Hispanic Black, Hispanic, and other), percentage poverty per zip code (0-10%, 10-20%, 20-30%, and 30+%), geographical characteristic (metropolitan/urban, micropolitan/large rural, and small/isolated rural town), and distance in meters away from the closest Title X family planning clinic (0-4000, 4000-7000, 7000-11000, 11000-15000, and 15000+ meters). Distance categories were based on the quintile distribution of abortion rates occurring from the ITOP file. The sum of all abortions per variable was calculated using Statistical Analysis System (SAS Institute, Inc., Cary, NC). The abortion rate per variable was analyzed using a Poisson model (SAS Proc Genmod) utilizing robust standard errors to account for multiple observations within each zip code area. The study was approved by the Emory University Institutional Review Board [8].

Statistical Methods. From the extracted data we calculated the pooled effect size in the form of SMD (standardized mean differences) for RCTs and two OS, and the pooled odd ratios for the remaining OS separately. All analyses were performed using the Comprehensive Meta-analysis version 3 software package (xxx.xxxx-xxxxxxxx.xxx). Comprehensive Meta-analysis version 3 includes a module that enables the analysis of multiple outcomes from the same study. For example, multiple outcomes analysis allows including effects of several outcomes accounting for correlation among the different outcomes whereas the same participants and the information for the different effects are not independent from each other. This module was used to derive an estimate for the overall cognitive outcomes. Heterogeneity among study point estimates was assessed with Q statistics with magnitude of heterogeneity being evaluated with the I2 index. Weighted mean effect sizes were computed under both fixed- and random-effects meta-analytic assumptions; homogeneity analyses (Q and I2) followed fixed-effects assumptions for combined analysis and random effects models for multiple outcomes analysis. Meta-regression was used to assess the effects of potential moderators.

Statistical Methods. This is a Phase 3 study designed to evaluate the XXX of MIRV in patients with high FRα expressing, high-grade PROC. All patients who have received at least 1 dose of MIRV will comprise the Safety Analysis Population. 1). The primary efficacy analysis of XXX and all other efficacy analyses will be based on the Efficacy Evaluable Population. The safety analysis will be based on Safety Analysis Population. All statistical analyses will be performed using SAS statistical software Version 9.4 or later, unless otherwise noted. For categorical variables, the number (n) and percent of each category within a parameter will be presented. For continuous variables, the sample size (n), mean, median, and standard deviation, as well as the minimum and maximum values, will be presented. Missing data will not be imputed unless otherwise stated. There will be a detailed description of patient disposition, patient demographics, and baseline characteristics.

Statistical Methods. ‌ A detailed SAP will be finalized before the primary database lock and unblinding. This analysis plan may modify what is outlined in the protocol; however, any major modifications of the primary endpoint definition or its analysis will also be reflected in a protocol amendment.