jtleek

# Load library
library(RSkittleBrewer)

# Differences in mean between 0 and 5
sig = seq(0,5,length=100)

# This is the sample size
ss = 20

# Calculate power from 200 replicated tests

jtleek

## See the paper by Jager and Leek and associated discussion
## for more information: http://biostatistics.oxfordjournals.org/content/15/1/1
## For the code to perform the analysis in that paper or to see how the p-values
## were collected see the repo: https://github.com/jtleek/swfdr

## The data for this gist are available here:
## https://github.com/jtleek/swfdr/blob/master/pvalueData.rda

## Load packages
library(ggplot2)

jtleek

## Load library/set seed
set.seed(1325)
library(qvalue)
library(RSkittleBrewer)
trop = RSkittleBrewer("tropical")

## Set a target p-value
target_pval = 0.8

## Not significant if we 

jtleek

Blah blah blah 2

jtleek

library(lubridate)
dt = "2015-11-18"
predict_function = function(dt){
dt_ymd = ymd(dt)

## Get some info
mday_dt = mday(dt_ymd)
wday_dt = wday(d_ymd)

## Download data

jtleek

col3 col2 col4 col1
h    b    t    t
i    w    i    g
k    t    g    n
n    h    n    i

jtleek

col3 col2 col4 col1
h    a    t    t
i    v    i    g
k    s    g    n
n    g    n    i

jtleek

col1 col3 col2
t    h    a
n    k    s
g    i    v
i    n    g

jtleek

#########################################################################################
#   Some functions to quantify your Google Scholar citations page. 
#   R functions Copyright (C) 2011 John Muschelli (jmuschel@jhsph.edu), Andrew Jaffe (ajaffe@jhsph.edu),
#   Jeffrey Leek (jtleek@gmail.com), and the Simply Statistics Blog
#   (http://simplystatistics.tumblr.com, http://twitter.com/simplystats)
#
#   This program is free software: you can redistribute it and/or modify
#   it under the terms of the GNU General Public License as published by
#   the Free Software Foundation, either version 3 of the License, or
#   (at your option) any later version.

jtleek

f1 = formula(log(cost) ~ date)
lm1 = lm(f1,data=nuclear)
stat = lm1$coeff[2]
resid = lm1$residuals
fit = lm1$fitted.values

n = dim(nuclear)[1]
B = 500
stat0 = rep(0,B)