Spss statistics for mac version 22

General estimating equations (GEE) and linear regression analyses were performed using IBM SPSS Statistics for Mac, Version 22.0 (IBM Corp., Armonk, NY, USA). Data describing the anthropometrical and biochemical parameters are presented as mean ± SD. The sample size was estimated using power analysis based on changes in fat mass in a pilot study of postmenopausal women on a PD. It was estimated that 30 participants were needed in each group to achieve P < 0.05 with 80% power. The effects of diet over time were analyzed using separate multiple regression models, each including diet group, time, and the group-by-time interaction as predictors. Regression parameters were estimated using GEE, a method that tolerates some degree of between-group variance. An exchangeable correlation structure was used to model the dependence between repeated measurements within participants. Prior to analysis, dependent variables with a skewed distribution were transformed using natural logarithms. Outcome is presented as P values for the included factors and estimated marginal means, with corresponding 95% confidence intervals for each diet at each time-point. P value of < 0.05 was considered statistically significant.

Levels of interobserver and intraobserver agreement were measured for each variable by the linear weighted kappa coefficient. Results were expressed as the median (range) for continuous variables, while frequencies and proportions (%) were used for ordinal FEES variables. The Mann–Whitney U test and the Chi-squared test were used for group comparisons. Spearman’s rho was used for correlations between continuous variables. All statistical analyses were performed with IBM SPSS Statistics for Mac, version 22.0 (Armonk, NY: IBM Corp.).

All data were analyzed using IBM SPSS Statistics for Mac, Version 22.0 (IBM Corp., Armonk, NY, USA). Two groups were compared using independent sample t-tests, and one-way analysis of variance (ANOVA) was used to compare three or more groups. In our experiment, a total of 5 pairs of self-control tissue samples were selected for whole transcriptome sequencing. In the qRT-PCR experiment, the differential expression of LINC02381 (21 pairs of tissues and 16 pairs of cells), miR-27b-3p (15 pairs of tissues and 12 pairs of cells) and CTNNB1 (15 pairs of tissues and 13 pairs of cells) were repeatedly tested. In CCK-8, Transwell, nucleocytoplasmic separation, RNA-FISH and Western blot experiments, there are at least three samples in each group. Differences were considered statistically significant at P < 0.05.

Descriptive statistics were conducted using WPS Office Excel for Mac version 3.3.0 (Kingsoft Office Corporation, Beijing, China). The influence of breeds on age-related factors and litter production, and the litter production of gilts with different first mating days were analyzed using Graphpad Prism 7.0 (Graphpad Software, inc.San Diego, CA, USA). Tukey’s multiple comparisons test of Ordinary one-way ANOVA was used to study the average utilization, estrus and first mating data of gilts’ batches among HP, IP and LP farms. The same method was used for litter production of HP, LP-Total, LP-BP and LP-CP farms. Normal distribution test of litter production at different first mating days of gilts were performed by SPSS Statistics software 22.0.0 (IBM Corp. Released 2013. IBM SPSS Statistics for Mac, Version 22.0. Armonk, NY). P < 0.05 showed significant difference.

All statistical analyses and tabulations were performed using IBM SPSS Statistics for Mac, version 22.0 (Armonk, NY: IBM Corp.).
Descriptive statistics: mean, standard deviation, median, minimum, maximum, skewness and kurtosis were calculated for each measure recorded. Parameters that were considered to have a normal distribution (skewness and kurtosis in the range >−3 and <+3) were compared using independent samples t tests; the others were compared using Mann-Whitney U tests.
The number and percentage of each morphological feature were recorded for livers in both populations. Population differences in morphology were analysed using Pearson’s chi square or Fisher's exact test, where cell counts were low (2 or less); in some cases, morphological categories were combined to produce adequate cell counts, where this was considered appropriate.