Statistical analysis results of post - pre training differences: NMR body mass, lean mass, fat mass, % lean mass, % fat mass; difference between terminal and pre-training NMR mass at 1W and 2W of endurance training; absolute VO\(_2\)max; relative VO\(_2\)max; and maximum run speed.
PRE_POST_STATSAn object of class data.frame with 90 rows and 21 columns:
character; the measurement being tested.
factor; the age of the rat at the beginning of the training protocol. Levels: "6M" (Adult) and "18M" (Aged).
factor; the sex of the rat with levels "Female" and "Male".
factor; exercise training group. Either "SED" (sedentary) or the number of weeks of training ("1W", "2W", "4W", "8W").
character; interpretation of the value in the
estimate column. Either "(post - pre) mean" (mean of the paired
(post - pre) differences) or "signed mean (post - pre) rank" (the signed
mean ranks of the (post - pre) differences).
numeric; the value of the estimate, as described by
estimate_type.
numeric; the standard error of the estimate.
numeric; lower bound of the 95% confidence interval.
numeric; upper bound of the 95% confidence interval.
character; the type of statistical test. Either "t" (Student's t-statistic) or "W" (Wilcox's W-statistic).
numeric; the value of the test statistic.
numeric; the p-value associated with the statistical test.
numeric; the Holm-adjusted p-value.
logical; TRUE if p.adj < 0.05.
character; the statistical model used for testing. Either "lm" (linear regression) or "wilcox.test" (Wilcoxon test).
character; the model formula. Includes the response variable, any transformations, and predictors.
character; the probability distribution and link function for the generalized linear model.
character; if reciprocal group variances were used as weights to account for heteroscedasticity (nonconstant residual variance), this is noted here.
character; if any observations were omitted during the analysis, they are listed here.
unique(PRE_POST_STATS$response)
#> [1] "Absolute VO2max" "Maximum Run Speed"
#> [3] "NMR % Fat" "NMR % Lean"
#> [5] "NMR Body Mass" "NMR Fat Mass"
#> [7] "NMR Lean Mass" "Relative VO2max"
#> [9] "Term - NMR Pre Body Mass"
head(PRE_POST_STATS)
#> # A tibble: 6 × 20
#> response age sex group estimate_type estimate SE lower.CL upper.CL
#> <chr> <fct> <fct> <fct> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 Absolute VO2… 6M Fema… SED (post - pre)… 0.131 0.339 -0.539 0.802
#> 2 Absolute VO2… 6M Fema… 4W (post - pre)… 0.504 0.263 -0.0157 1.02
#> 3 Absolute VO2… 6M Fema… 8W (post - pre)… 2.59 0.285 2.03 3.16
#> 4 Absolute VO2… 6M Male SED (post - pre)… -0.0677 0.339 -0.738 0.603
#> 5 Absolute VO2… 6M Male 4W (post - pre)… 0.796 0.277 0.248 1.34
#> 6 Absolute VO2… 6M Male 8W (post - pre)… 2.50 0.326 1.86 3.14
#> # ℹ 11 more variables: statistic_type <chr>, statistic <dbl>, df <dbl>,
#> # n <int>, p.value <dbl>, p.adj <dbl>, signif <lgl>, model_type <chr>,
#> # formula <chr>, weights <chr>, obs_removed <chr>