Sas stat software

The experimental data were analyzed using a joint randomized block design analysis as an approximation for simplicity. The analysis of variance was performed using the PROC GLM procedure of the SAS/STAT software (SAS Institute Inc., Cary, NC, USA). The linear model was
where y_ijk is the phenotype value of the k-th accession for the j-th replication in the i-th environment, μ is the population mean, t_i is the effect of the i-th environment, r_j(i) is the effect of the j-th replication in the i-th environment, g_k is the effect of the k-th accession, (gt)_ik is the interaction effect between accession and environment, and ε_ijk is the random error following N(0, σ²). Except that the effect of accession was considered fixed, all other effects were considered random. The trait heritability for the single environment and multiple environments was estimated, respectively, as
where ${\sigma }_g^2$ is the genotype variance, ${\sigma }_{gt}^2$ is the genotype and year interaction variance, σ² is the error variance, n_t is the number of years, and n_r is the number of replications. The variance components were estimated using the PROC MIXED procedure of the SAS/STAT software (SAS Institute Inc., Cary, NC, USA). The genetic coefficient of variation (GCV) was calculated as GCV = σ_g/μ.

Descriptive statistics were used to summarize children’s participation in YS for the primary social epidemiology study (n = 281) and the community trial sub-study (n = 215). Mixed-models were used to analyze the dichotomous outcome (i.e., 1 = Yes; 0 = No) of YS participation, and the continuous outcome of average minutes of daily MVPA. For all models, community was included as a random effect (34 (link)). SAS/STAT software, version 9.4 (^© 2002–2012) of the SAS System for Windows (Cary, NC), was used for all analyses. PROC GLIMMIX was performed to examine the dichotomous outcome of YS participation with the fixed effects of grade, sex, ethnoracial status, and family income. Interactions between the effects of grade, sex, ethnoracial status, and family income on YS participation were also explored. PROC MIXED was used to examine average minutes of daily MVPA with the fixed effects of grade, sex, ethnoracial status, family income, and YS participation. Similarly, interaction effects of grade, sex, ethnoracial status, family income, and YS participation on average time in MVPA were examined. Backward elimination of non-significant interactions based on statistical significance of p < 0.05 was used where non-significant higher order interactions were eliminated first, and then the models were refit (57 , 58 ).

Data are represented as number and percentage in parentheses (%) for categorical variables or mean (sd) for continuous variables.
Internal consistency for the nineteen UPFs included in the questionnaire was assessed by computing Cronbach’s α coefficient (considered satisfactory if higher than or equal to 0·70).
One-way χ² tests were used to assess differences between increased v. reduced consumption during lockdown as compared to before.
Regression models adjusted for age groups and sex were used to estimate the association of the UPF score (dependent variable) with demographic and socio-economic correlates; based on multivariable regression analysis (model 2), variables with P < 0·10 were included in the multivariable-adjusted regression models used to estimate the association of changes in UPF with lockdown-induced factors and diet-related modifications.
Missing data from categorical variables were assigned a missing indicator. For education, marital status, occupational class, number of cohabitants and living area (< 2 % of missing values) missing values were imputed to the cohort-specific modal value. All analyses were also separately performed for each cohort.
Statistical tests were two-sided, and P values < 0·05 were considered to indicate statistical significance.
Data analysis was generated using SAS/STAT software, version 9.4 (SAS Institute Inc.).

All data analyses were performed using SAS/STAT software (Cary, NC). Specimens with sufficient sample volume for completion of the CDC algorithm, the cobas HIV-1/HIV-2 Qual test, and alternate NAT (if required) were included in statistical analyses. Positive, negative, and overall percent agreements (PPA, NPA, and OPA) and associated 2-sided 95% Clopper-Pearson exact confidence intervals (CIs) for comparisons between assays and algorithms were calculated for each viral target (HIV-1 and HIV-2).

The data were analyzed using SAS/STAT software (version 9.4, SAS Institute Inc., Cary, NC). Feed intake and growth data were repeatedly measured using a mixed model that included fixed effects of forage, age, and the forage × age interaction and the random effects of the block and calves within the block. A total of 5 blocks were created. One-way ANOVA was used to analyze the fermentation parameters of the rumen and bacterial diversity. Statistically significant differences among groups were evaluated by Duncan's test. Differences were declared to be statistically significant at P < 0.05. Least squares means with the standard error of the means are reported.

Descriptive statistics were calculated to describe the sample characteristics. Weighted kappa statistics were utilized to examine the interrater agreement of ordinal auditory perceptual ratings between the two raters. The results were assessed as <0 indicating less than chance agreement, 0.01–0.20 as slight agreement, 0.21–0.40 as fair agreement, 0.41–0.60 as moderate agreement, 0.61–0.80 as substantial agreement, and 0.81–0.99 as almost perfect agreement [19 (link)]. Multiple regression analysis models were used to assess the relationships among each voice protocol variable as the outcome and each auditory-perceptual feature as the predictor controlling for sex and age at assessment. The analyses were conducted using SAS/STAT software (version 9.4, SAS System for Windows, SAS Institute Inc., Cary, NC, USA, 2012). All analyses were two-tailed with a p < 0.05 deemed as statistically significant.