## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup, echo=TRUE, message=FALSE, warning=FALSE--------------------------- library(tidyverse) library(bspam) data("passage2") ## ----desc1-------------------------------------------------------------------- passage2 %>% group_by(id.passage) %>% summarise(n.students = n(), numwords.pass = unique(numwords.pass), mean.wrc = mean(wrc), mean.sec = mean(sec)) %>% ungroup() %>% mutate(rate.wrc = mean.wrc/numwords.pass, mean.sec.per10 = mean.sec/numwords.pass*10) %>% knitr::kable(digits = 2) ## ----desc2-------------------------------------------------------------------- passage2 %>% group_by(id.student) %>% summarise(n.passages = n(), tot.wrc = sum(wrc), tot.sec = sum(sec), obs.wcpm = tot.wrc/tot.sec*60) %>% ungroup() %>% knitr::kable(digits = 2) ## ----calibration1, message=FALSE---------------------------------------------- MCEM_run1 <- fit.model(data = passage2, person.id = "id.student", task.id = "id.passage", max.counts = "numwords.pass", obs.counts = "wrc", time = "sec", k.in = 5, reps.in = 50, est = "mcem") ## ----------------------------------------------------------------------------- MCEM_run1 ## ----out1--------------------------------------------------------------------- MCEM_run1$task.param %>% knitr::kable(digits = 2) ## ----out2--------------------------------------------------------------------- MCEM_run1$hyper.param %>% knitr::kable(digits = 3) ## ----calibration2, eval=FALSE------------------------------------------------- # MCEM_run2 <- fit.model(data = passage2, # person.id = "id.student", # task.id = "id.passage", # max.counts = "numwords.pass", # obs.counts = "wrc", # time = "sec", # k.in = 5, # reps.in = 50, # est = "mcem", # se = "analytic") ## ----out3, eval=FALSE--------------------------------------------------------- # MCEM_run2$task.param %>% knitr::kable(digits = 2) ## ----out4, eval=FALSE--------------------------------------------------------- # MCEM_run2$hyper.param %>% knitr::kable(digits = 3) ## ----eval = FALSE------------------------------------------------------------- # WCPM_all <- scoring(calib.data=MCEM_run, # data = passage2, # person.id = "id.student", # occasion = "occasion", # group = "grade", # task.id = "id.passage", # max.counts = "numwords.pass", # obs.counts = "wrc", # time = "sec", # est = "map", # se = "analytic", # type="orf") # summary(WCPM_all)