![[Experimental]](figures/lifecycle-experimental.svg)
Arguments
- myfmts
A named list of either formatting specifications (ie stats with its associated formats) or a list of variables with formatting specifications.
- recursive
logical(1)Set toTRUEwhen requesting details from named list of variables with specifications. Set toFALSEwhen requesting details from named list of statistics with format specifications.- as_tibble
logical(1)WhenTRUE, convert the information into a tibble for ease of reviewing.- fmt1
A named list of formatting specifications (ie stats with its associated format)
- fmt2
Another named list of formatting specifications (ie stats with its associated format), to compare against
fmt1
Functions
get_fmt_details(): A utility function to collect information on formatting specification in list or tibble format.The following information is collected:
var (variable name): Only applicable if the format specification is a named list with formattings specs (eg list("AGE" = c("mean" = "xx", "se" = "xx.x"), "BMI" = c("mean" = "xx.x", "se" = "xx.xx"))), eg processed via
fmt_spec_var_dfunction.stat (name of statistic)
fun_fact : name of function factory that has produced the format specification (if spec is from formatting function, blank if spec is string).
Only the following known formatting functions are supported:jjcsformat_xx
jjcsformat_cnt_den_fract_fct,
jjcsformat_pval_fct,
jjcsformat_range_fct,
tern::format_xx,
tern::format_extreme_values,
tern::format_extreme_values_ci,
tern::format_count_fraction_fixed_dp,
tern::format_count_fraction,
tern::format_fraction_fixed_dp,
format_sigfig_j
str: string from specification, or str from formatting function factory (
jjcsformat_xx, ....)str_formatters: (
logical) Is the str value a valid format string as in (list_valid_format_labels())?type: when formatting function factory
jjcsformat_cnt_den_fract_fctis usedalpha: when formatting function factory
jjcsformat_pval_fctis usedmessage: Message when formatting function is unknown, or input string was not valid format string as in (
list_valid_format_labels())fmt_package: In which package was the formatting specification defined.
is_fun: (
logical) Is the formatting specification a function?round_type: (
logical) Does the formatting supportround_typeargument/behavior?fun: Formatting string or body of the formatting function.
Only when one of the formats provided is based upon formatting function factory
format_sigfig_jsetup:d: value used for
sigfigwhole_integer: value used for
whole_integerdrop0trailing: value used for
drop0trailingzero_threshold: value used for
zero_threshold
compare_fmt_specs(): A utility to report findings in differences between 2 formatting specification vectors. It returns a list object with the following information:spec1 : For statistics with a different specification, tibble with specification details from
fmt1.spec2 : For statistics with a different specification, tibble with specification details from
fmt2. The tibbles inspec1andspec2contain information as described inget_fmt_details().msg: Message on how many stats have a difference in specification.
comm_stats: Vector of stats in common between
fmt1andfmt2.diff_stats: Vector of stats with any difference identified.
Examples
# Example for get_fmt_details --
junco_def_d <- c(
"mean" = "xx.dx",
"mean_sd" = "xx.dx (xx.dxx)",
"range" = "(xx.d, xx.d)"
)
myfmts <- fmt_spec_single_d(
d = 1,
stats_in = c("mean", "mean_sd"),
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
fmt_details <- get_fmt_details(myfmts, as_tibble = TRUE)
myfmts2 <- fmt_spec_single_d(
d = 3,
stats_in = c("mean", "mean_sd"),
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
fmt_details2 <- get_fmt_details(myfmts2, as_tibble = TRUE)
fmt_details2
#> # A tibble: 2 × 11
#> stat fun_fact str str_formatters type alpha message fmt_package is_fun
#> <chr> <chr> <chr> <lgl> <chr> <chr> <chr> <chr> <lgl>
#> 1 mean "" xx.x… TRUE "" "" "" formatters FALSE
#> 2 mean_sd "jjcsform… xx.x… FALSE "" "" "" junco TRUE
#> # ℹ 2 more variables: round_type <lgl>, fun <named list>
# Example for get_fmt_details using format specs for variables --
# processed with fmt_spec_var_d
var <- c("AGE" = 0, "BMI" = 1, "BMRKR1" = 2)
vars_fmt <- fmt_spec_var_d(var,
stats_in = NULL,
fmt_d_def = junco_def_d,
fmt_d_in = NULL
)
fmt_details2 <- get_fmt_details(vars_fmt, as_tibble = TRUE, recursive = TRUE)
# Example for compare_fmt_specs --
test1_target <- junco_default_formats
# junco_def_d_all has been constructed with d = 1 as reference
# compare against junco_default_formats
test1_d <- fmt_spec_single_d(
d = 1,
stats_in = NULL,
fmt_d_def = junco_def_d_all,
fmt_d_in = NULL
)
check1 <- compare_fmt_specs(test1_d, test1_target)
#> 1 common stats with differences in specs
#> More details are available in created object.
check1
#> $spec1
#> # A tibble: 1 × 11
#> stat fun_fact str str_formatters type alpha message fmt_package is_fun
#> <chr> <chr> <chr> <lgl> <chr> <chr> <chr> <chr> <lgl>
#> 1 lr_stat_… jjcsfor… xx.x… FALSE "" "" "" junco TRUE
#> # ℹ 2 more variables: round_type <lgl>, fun <named list>
#>
#> $spec2
#> # A tibble: 1 × 11
#> stat fun_fact str str_formatters type alpha message fmt_package is_fun
#> <chr> <chr> <chr> <lgl> <chr> <chr> <chr> <chr> <lgl>
#> 1 lr_stat_… string xx.x… FALSE "" "" fmtfun… "" FALSE
#> # ℹ 2 more variables: round_type <lgl>, fun <named list>
#>
#> $msg
#> [1] "1 common stats with differences in specs"
#>
#> $comm_stats
#> [1] "adj_mean_se" "adj_mean_ci"
#> [3] "adj_mean_est_ci" "change"
#> [5] "cv" "diff"
#> [7] "diff_ci" "diff_est_ci"
#> [9] "diff_mean_se" "diff_mean_ci"
#> [11] "diff_mean_est_ci" "diff_means_n1"
#> [13] "diff_means_n2" "diff_means_est"
#> [15] "diff_means_se" "diff_means_est_se"
#> [17] "diff_means_ci" "diff_means_est_ci"
#> [19] "event_free_ci" "event_free_rate"
#> [21] "geom_sd" "geom_se"
#> [23] "geom_mean_sd" "geom_mean_se"
#> [25] "geom_cv" "geom_mean"
#> [27] "geom_mean_ci_3d" "hr"
#> [29] "hr_ci" "hr_ci_3d"
#> [31] "iqr" "quantiles_upper"
#> [33] "quantiles_lower" "lsmean"
#> [35] "lsmean_ci" "lsmean_diff"
#> [37] "lsmean_diff_with_ci" "lsmean_diff_ci"
#> [39] "lsmean_se" "mad"
#> [41] "mean" "mean_sd"
#> [43] "mean_se" "mean_ci_3d"
#> [45] "mean_diff_with_ci" "mean_pval"
#> [47] "median" "median_ci"
#> [49] "median_ci_3d" "median_range"
#> [51] "n" "n_tot"
#> [53] "n_tot_events" "or_ci"
#> [55] "pt_at_risk" "pval"
#> [57] "pvalue" "p_value"
#> [59] "quantiles" "range"
#> [61] "range_with_cens_info" "rate_ci"
#> [63] "rate_se" "rate_diff_ci_3d"
#> [65] "rel_risk_ci" "sd"
#> [67] "se" "n_altdf"
#> [69] "n_df" "n_rowdf"
#> [71] "n_parentdf" "denom"
#> [73] "count" "count_unique"
#> [75] "count_fraction" "count_fraction_fixed_dp"
#> [77] "count_unique_fraction" "count_unique_denom_fraction"
#> [79] "count_denom_frac" "count_frac"
#> [81] "unique_fraction" "rr_ci_3d"
#> [83] "patyrs" "eair"
#> [85] "eair_ci" "eair_est_ci"
#> [87] "eair_diff_est_ci" "eair_diff_est"
#> [89] "eair_diff_ci" "n_eair"
#> [91] "eair_n" "eair_n_py"
#> [93] "n_event" "person_years"
#> [95] "eair_strat" "n_event_total"
#> [97] "person_years_total" "n_eair_strat"
#> [99] "eair_strat_ci" "eair_strat_est_ci"
#> [101] "eair_strat_diff_est_ci" "total_subject_years"
#> [103] "n_fit" "unique"
#> [105] "sum" "sum_unique"
#> [107] "ratio" "ratio_unique"
#> [109] "ci" "fraction"
#> [111] "geom_mean_ci" "lr_stat_df"
#> [113] "max" "mean_ci"
#> [115] "mean_sdi" "mean_sei"
#> [117] "min" "n_blq"
#> [119] "n_events" "n_patients"
#> [121] "n_prop" "n_rate"
#> [123] "n_rsp" "n_unique"
#> [125] "nonunique" "or"
#> [127] "prop" "prop_ci"
#> [129] "pval_counts" "range_censor"
#> [131] "range_event" "rate"
#> [133] "rate_diff" "rate_diff_ci"
#> [135] "rate_ratio" "rate_ratio_ci"
#> [137] "riskdiff" "sum_exposure"
#> [139] "unique_count" "ztest_pval"
#>
#> $diff_stats
#> [1] "lr_stat_df"
#>
# more differences when using other d
test2_d <- fmt_spec_single_d(
d = 2,
stats_in = NULL,
fmt_d_def = junco_def_d_all,
fmt_d_in = NULL
)
check2 <- compare_fmt_specs(test2_d, test1_target)
#> 54 common stats with differences in specs
#> More details are available in created object.