Publications by Ching-Fang Wu
Week11 in-class exercise2
1 Introduction Teachers from a sample of 16 schools in California and Michigan were asked: “If you could go back to college and start all over again, would you again choose teaching as a profession?” The teachers’ perception of task variety was measured by the extent to which teachers followed the same routine each day. Source: Raudenbush, ...
981 sym R (7022 sym/38 pcs) 4 img
W12 in-class exercise3
1 Introduction The data are for 200 patients who had suffered from traumatic brain injuries resulting in comas of varying duration. After awakening from their comas, patients were administered a standard IQ test, on average, twice per patient. Source: Wong, P.P., Monette, G., & Weiner, N.I. (2001). Mathematical models of cognitive recovery. Brain...
1056 sym R (5509 sym/25 pcs) 4 img
Tutorial：Mixed-effect model (Simulation 2)
Bliese, P.D., Maltarich, M.A. & Hendricks, J.L. Back to Basics with Mixed-Effects Models: Nine Take-Away Points. J Bus Psychol 33, 1–23 (2018). https://doi.org/10.1007/s10869-017-9491-z 1 Data Management ##Simulation 2: Pure Group Data Simulate pure group-level data: This simulation relies on the sim.icc function in the multilevel library. li...
1536 sym R (4301 sym/42 pcs) 5 tbl
W2 Homework 4
Homework4 For the IQ and language example, plot 131 school-level regression lines of language score against verbal IQ (similar to the figure on the page). Compute the mean and standard deviation of the intercept and slope estimates. What is the correlation coefficient between the two parameter estimates? 1 IQ and language example The data set is...
1128 sym R (2939 sym/19 pcs) 2 img
W2 Homework 3
Homework3 Reproduce the plot on the NLSY 86 example by completing the R script using the data file in wide format. 1 Data management # input data dta <- read.csv("C:/Users/Ching-Fang Wu/Documents/data/nlsy86wide.csv") # inspect data structure str(dta) ## 'data.frame': 166 obs. of 23 variables: ## $ id : int 23901 25601 37401 4020...
272 sym R (7089 sym/17 pcs) 2 img
W2 in-class exercise 5
In-class exercise5： Draw a scatter plot of the variable normexam against the variable standLRT from the data set Exam{mlmRev}. Superimpose on it another scatter plot using the means of the same two variables by school. You can start by editing this rmarkdown template in RStudio before submitting the output to moodle. 1 Data management In this ...
1114 sym R (1327 sym/11 pcs) 1 img
W2 Homework 1
Exercises 1: Draw a scatter plot of the variables written and course scores from the data set Gcsemv{mlmRev} and superimpose another scatter plot on it using mean written and mean course scores by school as in the language and math example. You can start by editing in RStudio either the gcsemv rmarkdown or the exam rmarkdown file. 1 Data managem...
865 sym R (2134 sym/23 pcs) 1 img
W2 Homework 2
Homework2： In Rstudio, open and edit this R script from the SAT scores example to add an overall regression line of SAT score by teacher’s salary to three separate regression lines of the same set of variables by states with low, medium and high percentage of students taking the SAT exam. 1 Data management # input data dta <- read.table("ht...
397 sym R (2976 sym/14 pcs) 2 img
W2 in-class exercise 4
In-class exercise4： Download the data file from the language and math example first to a data folder. In Rstudio, open the R script and compile a report in html directly or use the command > knitr::spin(“foo.R”, knit=FALSE) to render it as an RMD file format first. 1 Introduction Ecological correlations are based on rates or averages. They...
942 sym R (1756 sym/12 pcs) 1 img
W2 in-class exercise 3
In-class exercise3：Reproduce the results in homework example using the rmarkdown file and publish it with a web link on the course moodle page. Introduction Kreft and de Leeuw (1998) obtained a sub-sample of students in eighth grade from the National Education Longitudinal Study of 1988 (NELS–88) collected by the National Center for Educatio...
899 sym R (3423 sym/15 pcs) 4 img