Table of content

1 Descriptive statistics

targets::tar_read(DB_IPAQ_0_12) |>
  dplyr::select(-n_visits) |>  
  dplyr::group_by(MONTH) |> 
  skimr::skim()
Data summary
Name dplyr::group_by(…)
Number of rows 154
Number of columns 3
_______________________
Column type frequency:
factor 1
numeric 1
________________________
Group variables MONTH

Variable type: factor

skim_variable MONTH n_missing complete_rate ordered n_unique top_counts
patient 0 0 1 FALSE 77 1: 1, 2: 1, 3: 1, 4: 1
patient 12 0 1 FALSE 77 1: 1, 2: 1, 3: 1, 4: 1

Variable type: numeric

skim_variable MONTH n_missing complete_rate mean sd p0 p25 p50 p75 p100 hist
MET_MIN_WK 0 0 1 5222.97 3627.95 876 3144 4539 6396 27960 ▇▃▁▁▁
MET_MIN_WK 12 0 1 4192.22 4722.84 0 1551 2796 5502 23106 ▇▃▁▁▁

2 Estimate of the median of the individual changes

tar_read(change_IPAQ_0_12)$hd_pbci_diff |> 
  dplyr::filter(q == 0.5) |> 
  dplyr::mutate(dplyr::across(estimate:ci_u, ~round(.x, digits = 2)))

3 Shift and difference asymmetry functions

targets::tar_read(change_IPAQ_0_12)$p
Change in IPAQ-SF MET-min/week between 6 and 12 months (N = 77). On panel A, the errors bars over the points are the standard deviations around the means, while on panel D it is the percentile bootstrap 95% confidence interval around the median estimate. On panels E and F, the error bars are percentile bootstrap 95% confidence intervals not corrected for multiple comparisons. On panels B, C and D, the horizontal and/or vertical segments are the estimates of the deciles (panels B and C) or the quantiles (panel D, step of 0.05) of the distributions; the thickest segments are the median estimates. On panel B, the diagonal black line depicts the identity line. If any, significant results (based on adjusted p-values) in the shift (panel E) and difference asymmetry (panel F) functions are highlighted using thick red circles. A small pseudo-random movement has been added horizontally and vertically to the raw data displayed on panel B to minimize the presence of points fully overlapped. The estimates of the deciles of the marginal distributions (panels B, C and D), the quantiles of the individual differences (panel D), the decile differences (panel E) and the quantile sums (panel F) have been computed using the Harrell-Davis estimator.

Change in IPAQ-SF MET-min/week between 6 and 12 months (N = 77). On panel A, the errors bars over the points are the standard deviations around the means, while on panel D it is the percentile bootstrap 95% confidence interval around the median estimate. On panels E and F, the error bars are percentile bootstrap 95% confidence intervals not corrected for multiple comparisons. On panels B, C and D, the horizontal and/or vertical segments are the estimates of the deciles (panels B and C) or the quantiles (panel D, step of 0.05) of the distributions; the thickest segments are the median estimates. On panel B, the diagonal black line depicts the identity line. If any, significant results (based on adjusted p-values) in the shift (panel E) and difference asymmetry (panel F) functions are highlighted using thick red circles. A small pseudo-random movement has been added horizontally and vertically to the raw data displayed on panel B to minimize the presence of points fully overlapped. The estimates of the deciles of the marginal distributions (panels B, C and D), the quantiles of the individual differences (panel D), the decile differences (panel E) and the quantile sums (panel F) have been computed using the Harrell-Davis estimator.