testmeansC {RCPA3}

One and two-sample difference of means tests (t-tests) with confidence intervals.

Description

Conducts one and two-sample difference of means tests (t-tests). Options for weighting observations, known population standard deviation, equal or unequal variances, paired observations.

Usage

testmeansC(x1, x2, w, data, dv, iv, digits = 2, var.equal = FALSE,
  paired = FALSE, pop.sd = FALSE, var.test = FALSE, printC = FALSE,
  ci.table = TRUE, ci.level = 95, ci.plot = TRUE, main, xlab, xlim, ...)

Arguments

x1

The first variable to be compared (mean of x1 will be compared to mean of x2). Must be numeric variable. Should be in the form dataset$var, unless dataset specified with data argument.

x2

The variable (or number) to which x1 is compared. Should be in the form dataset$var, unless dataset specified with data argument. You can set x2 equal to a number to conduct a one sample means test. For example, to test whether x1 could have population mean of 50, you'd set x2 = 50.

w

(Optional) Weights variable (optional). Should be in the form dataset$var, unless dataset specified with data argument.

data

(Optional) The dataset that contains x1, x1 and x2, or dv and iv.

dv

The dependent variable. Must be numeric variable. Should be in the form dataset$var, unless dataset specified with data argument.

iv

The independent variable. Should have two distinct values (like treatment and control). Should be in the form dataset$var, unless dataset specified with data argument.

digits

(Optional) Number of digits to report after decimal place, optional (default: 3).

var.equal

(Optional) With two-sample tests, do you want to assume equal variances? (default: FALSE)

paired

(Optional) With two-sample tests, are the observations paired? (default: FALSE)

pop.sd

(Optional) If the population standard deviation is known, you can specify it.

var.test

(Optional) If set to TRUE, will test the assumption that two sample variance are equal using an F test. Default is FALSE. The var.test option implemented for both weighted and unweighted analysis. If you are not using sample weights, you can supplement this F test with additional tests such as stats::bartlett.test and car::leveneTest.

printC

(Optional) Do you want results printed to .html file in your working directory? Default is FALSE. Set to TRUE to print results.

ci.table

(Optional) Confidence level for calculating the confidence interval of the difference of means, defaults to 95. Set to F or FALSE to omit confidence interval from results.

ci.level

(Optional) Desired confidence level, as percentage (default: 95)

ci.plot

(Optional) Do you want a plot of the confidence interval of the difference of means? (default: TRUE)

main

(Optional) Main title for plot of confidence interval of difference

xlab

(Optional) Label for x-axis of plot of confidence interval of difference

xlim

(Optional) A vector (of length 2) specifying the range of the x-axis, useful to zoom in on CI.

...

(Optional) Additional arguments passed to plot function for the CI plot

Value

No return

RCPA3 Package Tutorial Videos

• Testing Means with RCPA3 Package's testmeansC Function 12:22

• Complete Playlist of RCPA3 Package Tutorial Videos, includes video for this function and many more.

Textbook References

• Philip H. Pollock and Barry C. Edwards, An R Companion to Political Analysis, 3rd Edition (Thousand Oaks, CA: Sage Publications, Forthcoming 2022), Chapter 9.

• Philip H. Pollock and Barry C. Edwards, The Essentials of Political Analysis, 6th Edition (Thousand Oaks, CA: Sage Publications, 2020), pp.201-215. ISBN-13: 978-1506379616; ISBN-10: 150637961.

Online Resources

• R Tutorials & Resources for Hypothesis Tests with One and Two Samples, Compiled by Barry C. Edwards

• Sage Edge Resources for Political Analysis Series, for streaming videos, flashcards, and more student resources for textbooks by Pollock and Edwards, from Sage Publications.

• Political Science Data Web Site, find datasets for your own research and resources to help with the analysis.

Examples

   library(RCPA3)
   
    
   # one sample test against hypothesized value
   testmeansC(x1=world$literacy, x2=80)
   
   # with x1 and x2 
   testmeansC(x1=ft.trump.post, x2=ft.pence.post, w=wt, data=nes)
   
   # with paired x1 and x2
   testmeansC(x1=nes$ft.pence.post, x2=nes$ft.pence.pre, w=nes$wt, paired=TRUE)

   # with dv and iv 
   testmeansC(dv=nes$ft.bigbiz, iv=nes$gender, w=nes$wt)