#global options options( digits = 2, contrasts = c("contr.treatment", "contr.treatment") ) if (F) { devtools::install_github("merliseclyde/BAS") } #packages library(kirkegaard) load_packages( BAS, BMA, BMS, patchwork, readxl ) #ggplot2 theme_set(theme_bw())
#load SPI dataset spi = readxl::read_xlsx("inst/extdata/SPI2019.xlsx", sheet = 2) %>% df_legalize_names() #impute it insofar as reasonable, drop the rest spi_orig = spi spi = spi %>% miss_impute() #filter whatever is left with missing data spi = spi %>% miss_filter() #standardize everything for comparison spi = spi %>% df_standardize(exclude_range_01 = F)
#make up some semi-plausible model spi_model = str_glue("{names(spi)[34]} ~ {str_c(names(spi)[c(21:33, 37:40)], collapse = ' + ')}")
#fit a BAS model spi_bas_fit = BAS::bas.lm(spi_model, data = spi) spi_bas_fit spi_bas_fit %>% summary() (spi_bas_fit_coefs = spi_bas_fit %>% coef()) #test combined plot spi_bas_fit_coefs %>% GG_BMA()
#fit a BMA model spi_bma_fit = BMA::bic.glm(as.formula(spi_model), data = spi, glm.family = "gaussian") spi_bma_fit spi_bma_fit %>% GG_BMA()
#restyle the data since this package is annoying spi_bms = spi[, formula.tools::get.vars(as.formula(spi_model))] #fit a BMS model spi_bms_fit = BMS::bms(spi_bms) #coefs spi_bms_fit_coefs = spi_bms_fit %>% coef() spi_bms_fit %>% GG_BMA()
Input a data frame with the following columns: term, PIP, mean, sd
set.seed(1) made_up = tibble( term = LETTERS[1:10], PIP = runif(10), mean = rnorm(10, sd = .5), sd = runif(10, .1, .5) ) made_up %>% GG_BMA()
write_sessioninfo() #upload to OSF #avoid uploading the data in case they freak out again if (F) { library(osfr) #auth osf_auth(readr::read_lines("~/.config/osf_token")) #the project we will use osf_proj = osf_retrieve_node("https://osf.io/XXX/") #upload files #overwrite existing (versioning) osf_upload(osf_proj, conflicts = "overwrite", path = c( "figs", "data", "notebook.html", "notebook.Rmd", )) }
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.