From d23c6617c069c810e927b53f617ad9b7a7c8710c Mon Sep 17 00:00:00 2001 From: naeemkh Date: Thu, 15 Feb 2024 17:12:54 -0500 Subject: [PATCH] fix format --- README.md | 33 ++++++++++++++++----------------- 1 file changed, 16 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index 357718e0..c1572a8a 100755 --- a/README.md +++ b/README.md @@ -71,11 +71,10 @@ gps_obj <- estimate_gps(.data = m_d, where -**`.data`** A data.frame of input data including the `id` column. -**`.formula`** The formula for modeling exposure based on provided confounders. -**`sl_lib`**: A vector of prediction algorithms. -**`gps_density`** A model type which is used for estimating GPS value, including - normal (default) and kernel. +- `.data` A data.frame of input data including the `id` column. +- `.formula` The formula for modeling exposure based on provided confounders. +- `sl_lib` A vector of prediction algorithms. +- `gps_density` A model type which is used for estimating GPS value, including `normal` (default) and `kernel`. ### Computing weight or count of matched data @@ -94,17 +93,17 @@ cw_object_matching <- compute_counter_weight(gps_obj = gps_obj, where -**`ci_appr`** The causal inference approach. Possible values are: +- `ci_appr` The causal inference approach. Possible values are: - "matching": Matching by GPS - "weighting": Weighting by GPS -**`bin_seq`** Sequence of w (treatment) to generate pseudo population. If NULL is passed the default value will be used, which is `seq(min(w)+delta_n/2,max(w), by=delta_n)`. -**`nthread`** An integer value that represents the number of threads to be used by internal packages in a shared memory system. +- `bin_seq` Sequence of w (treatment) to generate pseudo population. If NULL is passed the default value will be used, which is `seq(min(w)+delta_n/2,max(w), by=delta_n)`. +- `nthread` An integer value that represents the number of threads to be used by internal packages in a shared memory system. If `ci.appr` = `matching`: - - *dist_measure*: Distance measuring function. Available options: + - `dist_measure`: Distance measuring function. Available options: - l1: Manhattan distance matching - - *delta_n*: caliper parameter. - - *scale*: a specified scale parameter to control the relative weight that + - `delta_n`: caliper parameter. + - `scale`: a specified scale parameter to control the relative weight that is attributed to the distance measures of the exposure versus the GPS. ### Estimating psuedo population @@ -122,10 +121,10 @@ pseudo_pop_matching <- generate_pseudo_pop(.data = m_d, where -**covar_bl_method**: covariate balance method. Available options: +- `covar_bl_method`: covariate balance method. Available options: - 'absolute' -**covar_bl_trs**: covariate balance threshold -**covar_bl_trs_type**: covariate balance type (mean, median, maximal) +- `covar_bl_trs`: covariate balance threshold +- `covar_bl_trs_type`: covariate balance type (mean, median, maximal) ### Estimating exposure response function @@ -145,9 +144,9 @@ erf_obj_nonparametric <- estimate_erf(.data = pseudo_pop_matching$.data, where -**`w_vals`**: A numeric vector of values at which you want to calculate the exposure response function. -**`bw_seq`**: A vector of bandwidth values. -**`kernel_appr`**: Internal kernel approach. Available options are locpol and kernsmooth. +- `w_vals`: A numeric vector of values at which you want to calculate the exposure response function. +- `bw_seq`: A vector of bandwidth values. +- `kernel_appr`: Internal kernel approach. Available options are locpol and kernsmooth. ## Notes