首先，加载所示的三个库。然后在下一个代码块中拟合ANOVA，用数据中的其他p值/xy位置拟合Tukey检验，...
首先，加载所示的三个库。然后在下一个代码块中拟合ANOVA，用数据中的其他p值/xy位置拟合Tukey检验，...
可以使用label = "p = {scales::pvalue(p.adj)}"
可以使用label = "p = {scales::pvalue(p.adj)}"
(p.adj, digits = 2)) # Create a boxplot and add custom p-value ggboxplot(df, x = "supp", y = "len", ggtheme = theme_bw())+ facet_wrap(~dose) + geom_signif( data=anno_df, aes(xmin = group1, xmax = group2, annotations = p.adj, y_position = y_pos), manual= TRUE...
系统管理——》全局安全配置 ——》授权策略 ——》选择 Role-Based Strategy
Den DF 8 ProbF Num 8 PVALUE6.4 Pr > F 9 PValue Num 8 PVALUE6.4 P-Value The following statements create a new data set that contains the two data sets created in the preceding PROC GLM step and display the results in Output 20.7.2: title2 'The Combined Data Set'; data temp1; ...
add columns for the month, principal paid, indicator of PMI and PMI cost schedule = schedule %>% dplyr::mutate( month = 0:(dplyr::n()-1), principal = payment - interest ) schedule = schedule %>% dplyr::mutate( has_pmi = balance > pmi_cutoff, pmi = ifelse(has_pmi, pmi_value,...
而费舍尔精确检验在分析对应的p值时没有做任何的近似处理，所以称其计算出来的p值很精确。
$p.value <- p.adjust(diff$p.value,"bonferroni")# diff <- diff %>% filter(p.value <0.05)# 非参检验# wilcox testlibrary(tidyverse)diff <- data1 %>%select_if(is.numeric) %>%map_df(~ broom::tidy(wilcox.test(. ~ Group,data = data1, conf.int= TRUE)), .id ='var')diff$p....