Publications by Dr. B
MVS Module 6 Handout - Intro to Logistic Regression
Multivariate Statistics: Module 6 - Intro to Logistic Regression Author Dr. Broda Load in a few packages library(tidyverse) ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ✔ dplyr 1.1.4 ✔ readr 2.1.5 ✔ forcats 1.0.0 ✔ stringr ...
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Module 2 Handout - Review of Linear Regression
Load a Few Packages: library(tidyverse) library(ggplot2) library(broom) library(skimr) Input the Food Dataset (from reading): food <- read_csv("food.csv") Parsed with column specification: cols( FOODCONSUMPTION = [32mcol_number()[39m, FAMILYINCOME = [32mcol_number()[39m, NUMCHULDREN = [32mcol_double()[39m, HAVEGARDEN = [31mcol_character(...
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Module 1 Content Review
Load in Useful Packages library(haven) library(psych) Attaching package: ‘psych’ The following objects are masked from ‘package:ggplot2’: %+%, alpha library(tidyverse) Load in the Dataset and Glimpse hsb2 <- read_dta("hsb2.dta") glimpse(hsb2) Rows: 200 Columns: 11 $ id [3m[38;5;246m<dbl>[39m[23m 70, 121, 86, 141, 172, 113, 50...
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Module 1 Demonstration
Load in Some Useful R Packages library(tidyverse) library(psych) library(haven) Load in the Data gss <- read_dta("descriptive_gss.dta") glimpse(gss) Rows: 2,765 Columns: 16 $ id [3m[38;5;246m<dbl>[39m[23m 2331, 2003, 1221, 2051, 2465, 546, 1291, 732, 303, 2700, 855, 623, 159, 886, 2036, 27… $ hrs1 [3m[38;5;246m<dbl+lbl>[39m[23m NA, ...
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MLM Module 3 Demonstration
This week, we are going to use a larger version of the HSB dataset back from 1988. Same structure- students nested within schools. This is the same dataset that Garson uses in Chapter 3, so you can recreate what he has as well. Load Some Packages to Help with the Analysis and Data Management: library(tidyverse) library(Hmisc) # label() library(...
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Module 4 Demonstration
This week, we are going to use data from Gavin and Hofmann (2002), a study on organizational climate and attitudes published in Leadership Quarterly. Here, we have individuals soldiers nested within companies. This is the same dataset that Garson uses in Chapter 6, so you can recreate his analysis. Load Some Packages to Help with the Analysis an...
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MLM Module 8 Demonstration - Intro to Growth Models
This week, we go to a dataset collected as part of the US Sustaining Effects Study (Carter 1984), which attemtped to assess the sustaining impacts of compensatory schooling for students over time. Load in Our MVP Packages suppressPackageStartupMessages(library(tidyverse)) package ‘ggplot2’ was built under R version 3.6.2package ‘tibble’ ...
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MLM Week 7 Demo - Intro to 3-Level Models
This week, we are going to use the Kindergarten data from Project STAR, the Tennessee Class Size Experiment conducted from 1985-1990. Load Some Packages to Help with the Analysis and Data Management: suppressPackageStartupMessages(library(tidyverse)) package ‘tibble’ was built under R version 3.6.2package ‘dplyr’ was built under R versio...
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MLM Module 5 Demonstration - Random Slopes and Cross-Level Interactions
This week, we are going to use data from Gavin and Hofmann (2002), a study on organizational climate and attitudes published in Leadership Quarterly. Here, we have individuals soldiers nested within companies. This is the same dataset that Garson uses in Chapter 6, so you can recreate his analysis. Load Some Packages to Help with the Analysis an...
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MLM Module 5 Content Review - Key
This week, we will use schoolsmoke dataset that we worked with in class. The data are from the Television, School, and Family Smoking Prevention and Cessation Project (Flay et al. 1988; Rabe-Hesketh and Skrondal 2012, chap. 11), a schoolwide anti-smoking intervention where schools were randomly assigned into a schoolwide curricular intervention ...
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