mjadkins’s gists

mjadkins / gist:bf9295c24c70f282b536fd399f3c2a15

Created February 26, 2020 13:42

	odds_to_rr <-function (fit)
	{
	Estimates <- fixef(fit)
	param <-data.frame(Estimates)
	param$Parameter <- row.names(param)
	est <- param %>% select(Parameter, Estimates)
	rownames(est) <- NULL
	est[[2]] <- exp(est[[2]])
	ci <- stats::confint(fit, method = "Wald", parm = "beta_")
	else ci <- stats::confint(fit)

mjadkins / R_AWS_Load_Auto.R

Last active October 6, 2016 18:38

	#!/bin/bash

	# Update Ubuntu
	sudo apt-get update

	# Install gcc and clang C++ compilers
	sudo apt-get install gcc
	sudo apt-get install clang

	#Install libcurl4

mjadkins / R_AWS.R

Last active October 6, 2016 09:39

R and RSTAN on Amazon Web Services Elastic Cloud Computing (EC2) using Ubuntu Linux Server - October 2016

	# In your terminal navigate to key pair
	cd <your directory>

	# Connect to the server via Secure Shell (SSH)
	ssh -i YOUR_KEYPAIR.pem.txt ubuntu@PUBLIC_DNS

	# You may get an error so you will need to modify the key
	chmod 600 YOUR_KEYPAIR.pem.txt

	# Connect to the server via Secure Shell (SSH)

mjadkins / ggplot2_caterpillar_2.R

Created April 9, 2016 17:03

	# Load libraries
	lapply(c("R2MLwiN","arm","ggplot2","RColorBrewer","grid"),library, character.only=TRUE)

	# Set working directory and load data
	setwd("~/R")
	data(tutorial)
	str(tutorial)

	# Fit a linear varying intercept multilevel model with group level predictors of normexam ~ sex + standlrt + vrband + schgend + avslrt + schav + (1\|school)
	fit.1 <-lmer(normexam ~ sex + standlrt + vrband + schgend + avslrt + schav + (1\|school), data=tutorial)

mjadkins / ggplot2_caterpillar.R

Created August 9, 2015 19:13

ggplot2 Caterpillar Plot

	# Load libraries
	lapply(c("R2MLwiN","arm","ggplot2","RColorBrewer","grid"),library, character.only=TRUE)

	# Set working directory and load data
	setwd("~/R")
	data(tutorial)
	str(tutorial)

	# Fit a linear varying intercept multilevel model with group level predictors of normexam ~ sex + standlrt + vrband + schgend + avslrt + schav + (1\|school)
	fit.1 <-lmer(normexam ~ sex + standlrt + vrband + schgend + avslrt + schav + (1\|school), data=tutorial)

mjadkins / ggplot2_coefplot.R

Last active September 21, 2015 19:34

ggplot2_coefplot

	# Load libraries
	lapply(c("datasets","arm","ggplot2","RColorBrewer","grid"),library, character.only=TRUE)

	# Set working directory and load data
	setwd("~/R")
	data(mtcars)

	# Fit a linear model of mpg ~ wt + disp + hp + qsec
	fit.1 <-lm(mpg ~ wt + disp + hp + qsec, data=mtcars)
	display(fit.1)

mjadkins / gist:b68b7510e63a28d425ea

Last active August 29, 2015 14:26 — forked from abelsonlive/gist:3899832

coefplot.R


	require("RColorBrewer")
	# not run:
	# model = lm(y~x1+x2+x3+x4...)

	# Construct quantile table for varialbes of interest
	# t value: n-p=df.residual=634, alpha=5%,50%. t(1-alpha/2, n-p)
	t.05 <- qt(1-0.025, 634, lower.tail = TRUE, log.p=FALSE)
	t.5 <- qt(1-0.25, 634, lower.tail = TRUE, log.p=FALSE)
	coef.quantil <- data.frame(matrix(0, nrow=length(model$coefficients)-1, ncol=8))

MJ mjadkins