docs/MixedVignette.md

In cwendorf/EASIalt: easiOrigin

Mixed Vignette

This vignette analyzes data from a two-factor mixed design.

• Data Management
• Data Entry
• Descriptive Statistics
• Analyses of the Means
• Confidence Intervals
• Significance Tests
• Analyses of the Effects
• Source Table
• Significance Test
• Effect Size

Data Management

Data Entry

Factor <- c(1,1,1,1,2,2,2,2)
Outcome1 <- c(0,0,3,5,1,3,6,6)
Outcome2 <- c(4,7,4,9,3,1,6,6)
Outcome3 <- c(4,9,6,9,3,3,6,8)
Factor <- factor(Factor,levels=c(1,2),labels=c("Level1","Level2"))
MixedData <- data.frame(Factor,Outcome1,Outcome2,Outcome3)
MixedData

##   Factor Outcome1 Outcome2 Outcome3
## 1 Level1        0        4        4
## 2 Level1        0        7        9
## 3 Level1        3        4        6
## 4 Level1        5        9        9
## 5 Level2        1        3        3
## 6 Level2        3        1        3
## 7 Level2        6        6        6
## 8 Level2        6        6        8

Descriptive Statistics

descMeansBy(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Descriptive Statistics for the Data: Level1`
##                N       M      SD
## Outcome1   4.000   2.000   2.449
## Outcome2   4.000   6.000   2.449
## Outcome3   4.000   7.000   2.449
## 
## $`Descriptive Statistics for the Data: Level2`
##                N       M      SD
## Outcome1   4.000   4.000   2.449
## Outcome2   4.000   4.000   2.449
## Outcome3   4.000   5.000   2.449

Analyses of the Means

Confidence Intervals

ciMeansBy(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Confidence Intervals for the Means: Level1`
##                M      SE      df      LL      UL
## Outcome1   2.000   1.225   9.000  -0.771   4.771
## Outcome2   6.000   1.225   9.000   3.229   8.771
## Outcome3   7.000   1.225   9.000   4.229   9.771
## 
## $`Confidence Intervals for the Means: Level2`
##                M      SE      df      LL      UL
## Outcome1   4.000   1.225   9.000   1.229   6.771
## Outcome2   4.000   1.225   9.000   1.229   6.771
## Outcome3   5.000   1.225   9.000   2.229   7.771

ciMeansBy(cbind(Outcome1,Outcome2,Outcome3),by=Factor,conf.level=.99)

## $`Confidence Intervals for the Means: Level1`
##                M      SE      df      LL      UL
## Outcome1   2.000   1.225   9.000  -1.980   5.980
## Outcome2   6.000   1.225   9.000   2.020   9.980
## Outcome3   7.000   1.225   9.000   3.020  10.980
## 
## $`Confidence Intervals for the Means: Level2`
##                M      SE      df      LL      UL
## Outcome1   4.000   1.225   9.000   0.020   7.980
## Outcome2   4.000   1.225   9.000   0.020   7.980
## Outcome3   5.000   1.225   9.000   1.020   8.980

Significance Tests

nhstMeansBy(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Hypothesis Tests for the Means: Level1`
##             Diff      SE       t      df       p
## Outcome1   2.000   1.225   1.633   9.000   0.137
## Outcome2   6.000   1.225   4.899   9.000   0.001
## Outcome3   7.000   1.225   5.715   9.000   0.000
## 
## $`Hypothesis Tests for the Means: Level2`
##             Diff      SE       t      df       p
## Outcome1   4.000   1.225   3.266   9.000   0.010
## Outcome2   4.000   1.225   3.266   9.000   0.010
## Outcome3   5.000   1.225   4.082   9.000   0.003

nhstMeansBy(cbind(Outcome1,Outcome2,Outcome3),by=Factor,mu=5)

## $`Hypothesis Tests for the Means: Level1`
##             Diff      SE       t      df       p
## Outcome1  -3.000   1.225  -2.449   9.000   0.037
## Outcome2   1.000   1.225   0.816   9.000   0.435
## Outcome3   2.000   1.225   1.633   9.000   0.137
## 
## $`Hypothesis Tests for the Means: Level2`
##             Diff      SE       t      df       p
## Outcome1  -1.000   1.225  -0.816   9.000   0.435
## Outcome2  -1.000   1.225  -0.816   9.000   0.435
## Outcome3   0.000   1.225   0.000   9.000   1.000

Analyses of the Effects

Source Table

descMultifactor(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Source Table for the Effects: Between Subjects`
##                SS      df      MS
## Factor      2.667   1.000   2.667
## Residuals  88.000   6.000  14.667
## 
## $`Source Table for the Effects: Within Subjects`
##                      SS      df      MS
## Measures         37.333   2.000  18.667
## Measures:Factor  21.333   2.000  10.667
## Residuals        20.000  12.000   1.667

Significance Test

nhstMultifactor(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Hypothesis Tests for the Effects: Between Subjects`
##                 F      df       p
## Factor      0.182   1.000   0.685
## Residuals      NA   6.000      NA
## 
## $`Hypothesis Tests for the Effects: Within Subjects`
##                       F      df       p
## Measures         11.200   2.000   0.002
## Measures:Factor   6.400   2.000   0.013
## Residuals            NA  12.000      NA

Effect Size

pvaMultifactor(cbind(Outcome1,Outcome2,Outcome3),by=Factor)

## $`Proportion of Variance Accounted for by the Effects: Between Subjects`
##             EtaSq ParEtaSq
## Factor      0.029    0.029
## Residuals   0.971       NA
## 
## $`Proportion of Variance Accounted for by the Effects: Within Subjects`
##                   EtaSq ParEtaSq
## Measures          0.475    0.651
## Measures:Factor   0.271    0.516
## Residuals         0.254       NA

cwendorf/EASIalt documentation built on Oct. 31, 2023, 1:20 a.m.