#+TITLE: Rapport package team
#+AUTHOR: ANOVA Template
#+DATE: 2011-04-26 20:25 CET
** Description
An ANOVA report with table of descriptives, diagnostic tests and
ANOVA-specific statistics.
*** Introduction
*Analysis of Variance* or *ANOVA* is a statistical procedure that tests
equality of means for several samples. It was first introduced in 1921
by famous English statistician Sir Ronald Aylmer Fisher.
*** Model Overview
One-Way ANOVA was carried out, with /Gender/ as independent variable,
and /Internet usage in leisure time (hours per day)/ as a response
variable. Factor interaction was taken into account.
*** Descriptives
In order to get more insight on the model data, a table of frequencies
for ANOVA factors is displayed, as well as a table of descriptives.
**** Frequency Table
Below lies a frequency table for factors in ANOVA model. Note that the
missing values are removed from the summary.
| gender | N | % | Cumul. N | Cumul. % |
|----------+-------+---------+------------+------------|
| male | 410 | 60.92 | 410 | 60.92 |
| female | 263 | 39.08 | 673 | 100 |
| Total | 673 | 100 | 673 | 100 |
**** Descriptive Statistics
The following table displays the descriptive statistics of ANOVA model.
Factor levels lie on the left-hand side, while the corresponding
statistics for response variable are given on the right-hand side.
| Gender | Min | Max | Mean | Std.Dev. | Median | IQR |
|----------+-------+-------+---------+------------+----------+-------|
| male | 0 | 12 | 3.27 | 1.953 | 3 | 3 |
| female | 0 | 12 | 3.064 | 2.355 | 2 | 3 |
#+CAPTION: Table continues below
| Skewness | Kurtosis |
|------------+------------|
| 0.9443 | 0.9858 |
| 1.398 | 1.87 |
*** Diagnostics
Before we carry out ANOVA, we'd like to check some basic assumptions.
For those purposes, normality and homoscedascity tests are carried out
alongside several graphs that may help you with your decision on model's
main assumptions.
**** Diagnostics
***** Univariate Normality
| Method | Statistic | p-value |
|--------------------------------------------------+-------------+-------------|
| Lilliefors (Kolmogorov-Smirnov) normality test | 0.168 | 3e-52 |
| Anderson-Darling normality test | 18.75 | 7.261e-44 |
| Shapiro-Wilk normality test | 0.9001 | 1.618e-20 |
So, the conclusions we can draw with the help of test statistics:
- based on /Lilliefors test/, distribution of /Internet usage in
leisure time (hours per day)/ is not normal
- /Anderson-Darling test/ confirms violation of normality assumption
- according to /Shapiro-Wilk test/, the distribution of /Internet usage
in leisure time (hours per day)/ is not normal
As you can see, the applied tests confirm departures from normality of
the Internet usage in leisure time (hours per day).
***** Homoscedascity
In order to test homoscedascity, /Bartlett/ and /Fligner-Kileen/ tests
are applied.
| Method | Statistic | p-value |
|----------------------------------------------------+-------------+------------|
| Fligner-Killeen test of homogeneity of variances | 0.4629 | 0.4963 |
| Bartlett test of homogeneity of variances | 10.77 | 0.001032 |
When it comes to equality of variances, applied tests yield inconsistent
results. While /Fligner-Kileen test/ confirmed the hypotheses of
homoscedascity, /Bartlett's test/ rejected it.
**** Diagnostic Plots
Here you can see several diagnostic plots for ANOVA model:
- residuals against fitted values
- scale-location plot of square root of residuals against fitted values
- normal Q-Q plot
- residuals against leverages
[[plots/ANOVA-5-hires.png][[[plots/ANOVA-5.png]]]]
*** ANOVA Summary
**** ANOVA Table
| | Df | Sum.Sq | Mean.Sq | F.value | Pr..F. |
|---------------+-------+----------+-----------+-----------+----------|
| *gender* | 1 | 6.422 | 6.422 | 1.43 | 0.2322 |
| *Residuals* | 636 | 2856 | 4.49 | | |
/F-test/ for /Gender/ is not statistically significant, which implies
that there is no Gender effect on response variable.
**** Post Hoc test
***** Results
After getting the results of the ANOVA, usually it is advisable to run a
[[http://en.wikipedia.org/wiki/Post-hoc_analysis][post hoc test]] to
explore patterns that were not specified a priori. Now we are presenting
[[http://en.wikipedia.org/wiki/Tukey%27s_range_test][Tukey's HSD test]].
****** gender
| | Difference | Lower Bound | Upper Bound |
|-----------------+--------------+---------------+---------------|
| *female-male* | -0.206 | -0.543 | 0.132 |
#+CAPTION: Table continues below
| | P value |
|-----------------+-----------|
| *female-male* | /0.232/ |
There are no categories which differ significantly here.
***** Plot
Below you can see the result of the post hoc test on a plot.
[[plots/ANOVA-6-hires.png][[[plots/ANOVA-6.png]]]]
** Description
An ANOVA report with table of descriptives, diagnostic tests and
ANOVA-specific statistics.
*** Introduction
*Analysis of Variance* or *ANOVA* is a statistical procedure that tests
equality of means for several samples. It was first introduced in 1921
by famous English statistician Sir Ronald Aylmer Fisher.
*** Model Overview
Two-Way ANOVA was carried out, with /Gender/ and /Relationship status/
as independent variables, and /Internet usage in leisure time (hours per
day)/ as a response variable. Factor interaction was taken into account.
*** Descriptives
In order to get more insight on the model data, a table of frequencies
for ANOVA factors is displayed, as well as a table of descriptives.
**** Frequency Table
Below lies a frequency table for factors in ANOVA model. Note that the
missing values are removed from the summary.
| gender | partner | N | % | Cumul. N | Cumul. % |
|----------+---------------------+-------+---------+------------+------------|
| male | in a relationship | 150 | 23.7 | 150 | 23.7 |
| female | in a relationship | 120 | 18.96 | 270 | 42.65 |
| male | married | 33 | 5.213 | 303 | 47.87 |
| female | married | 29 | 4.581 | 332 | 52.45 |
| male | single | 204 | 32.23 | 536 | 84.68 |
| female | single | 97 | 15.32 | 633 | 100 |
| Total | Total | 633 | 100 | 633 | 100 |
**** Descriptive Statistics
The following table displays the descriptive statistics of ANOVA model.
Factor levels and their combinations lie on the left-hand side, while
the corresponding statistics for response variable are given on the
right-hand side.
| Gender | Relationship status | Min | Max | Mean | Std.Dev. |
|----------+-----------------------+-------+-------+---------+------------|
| male | in a relationship | 0.5 | 12 | 3.058 | 1.969 |
| male | married | 0 | 8 | 2.985 | 2.029 |
| male | single | 0 | 10 | 3.503 | 1.936 |
| female | in a relationship | 0.5 | 10 | 3.044 | 2.216 |
| female | married | 0 | 10 | 2.481 | 1.967 |
| female | single | 0 | 12 | 3.323 | 2.679 |
#+CAPTION: Table continues below
| Median | IQR | Skewness | Kurtosis |
|----------+--------+------------+------------|
| 2.5 | 2 | 1.324 | 2.649 |
| 3 | 2 | 0.862 | 0.1509 |
| 3 | 3 | 0.7574 | 0.08749 |
| 3 | 3 | 1.383 | 1.831 |
| 2 | 1.75 | 2.063 | 5.586 |
| 3 | 3.5 | 1.185 | 0.9281 |
*** Diagnostics
Before we carry out ANOVA, we'd like to check some basic assumptions.
For those purposes, normality and homoscedascity tests are carried out
alongside several graphs that may help you with your decision on model's
main assumptions.
**** Diagnostics
***** Univariate Normality
| Method | Statistic | p-value |
|--------------------------------------------------+-------------+-------------|
| Lilliefors (Kolmogorov-Smirnov) normality test | 0.168 | 3e-52 |
| Anderson-Darling normality test | 18.75 | 7.261e-44 |
| Shapiro-Wilk normality test | 0.9001 | 1.618e-20 |
So, the conclusions we can draw with the help of test statistics:
- based on /Lilliefors test/, distribution of /Internet usage in
leisure time (hours per day)/ is not normal
- /Anderson-Darling test/ confirms violation of normality assumption
- according to /Shapiro-Wilk test/, the distribution of /Internet usage
in leisure time (hours per day)/ is not normal
As you can see, the applied tests confirm departures from normality of
the Internet usage in leisure time (hours per day).
***** Homoscedascity
In order to test homoscedascity, /Bartlett/ and /Fligner-Kileen/ tests
are applied.
| Method | Statistic | p-value |
|----------------------------------------------------+-------------+-------------|
| Fligner-Killeen test of homogeneity of variances | 1.123 | 0.2892 |
| Bartlett test of homogeneity of variances | 11.13 | 0.0008509 |
When it comes to equality of variances, applied tests yield inconsistent
results. While /Fligner-Kileen test/ confirmed the hypotheses of
homoscedascity, /Bartlett's test/ rejected it.
**** Diagnostic Plots
Here you can see several diagnostic plots for ANOVA model:
- residuals against fitted values
- scale-location plot of square root of residuals against fitted values
- normal Q-Q plot
- residuals against leverages
[[plots/ANOVA-7-hires.png][[[plots/ANOVA-7.png]]]]
*** ANOVA Summary
**** ANOVA Table
| | Df | Sum.Sq | Mean.Sq | F.value |
|--------------------+-------+----------+-----------+-----------|
| *gender* | 1 | 4.947 | 4.947 | 1.085 |
| *partner* | 2 | 31.21 | 15.61 | 3.424 |
| *gender:partner* | 2 | 3.038 | 1.519 | 0.3332 |
| *Residuals* | 593 | 2703 | 4.558 | |
#+CAPTION: Table continues below
| | Pr..F. |
|--------------------+-----------|
| *gender* | 0.2979 |
| *partner* | 0.03324 |
| *gender:partner* | 0.7168 |
| *Residuals* | |
/F-test/ for /Gender/ is not statistically significant, which implies
that there is no Gender effect on response variable. Effect of
/Relationship status/ on response variable is significant. Interaction
between levels of /Gender/ and /Relationship status/ wasn't found
significant (p = 0.717).
**** Post Hoc test
***** Results
After getting the results of the ANOVA, usually it is advisable to run a
[[http://en.wikipedia.org/wiki/Post-hoc_analysis][post hoc test]] to
explore patterns that were not specified a priori. Now we are presenting
[[http://en.wikipedia.org/wiki/Tukey%27s_range_test][Tukey's HSD test]].
****** gender
| | Difference | Lower Bound | Upper Bound |
|-----------------+--------------+---------------+---------------|
| *female-male* | -0.186 | -0.538 | 0.165 |
#+CAPTION: Table continues below
| | P value |
|-----------------+-----------|
| *female-male* | /0.298/ |
There are no categories which differ significantly here.
****** partner
| | Difference | Lower Bound |
|-------------------------------+--------------+---------------|
| *married-in a relationship* | -0.289 | -1.012 |
| *single-in a relationship* | 0.371 | -0.061 |
| *single-married* | 0.66 | -0.059 |
#+CAPTION: Table continues below
| | Upper Bound | P value |
|-------------------------------+---------------+-----------|
| *married-in a relationship* | 0.435 | /0.616/ |
| *single-in a relationship* | 0.803 | /0.109/ |
| *single-married* | 1.379 | /0.079/ |
There are no categories which differ significantly here.
****** gender:partner
| | Difference | Lower Bound |
|-----------------------------------------------------+--------------+---------------|
| *female:in a relationship-male:in a relationship* | -0.014 | -0.777 |
| *male:married-male:in a relationship* | -0.073 | -1.25 |
| *female:married-male:in a relationship* | -0.577 | -1.877 |
| *male:single-male:in a relationship* | 0.444 | -0.23 |
| *female:single-male:in a relationship* | 0.264 | -0.545 |
| *male:married-female:in a relationship* | -0.059 | -1.266 |
| *female:married-female:in a relationship* | -0.563 | -1.89 |
| *male:single-female:in a relationship* | 0.459 | -0.267 |
| *female:single-female:in a relationship* | 0.279 | -0.574 |
| *female:married-male:married* | -0.504 | -2.105 |
| *male:single-male:married* | 0.518 | -0.635 |
| *female:single-male:married* | 0.338 | -0.899 |
| *male:single-female:married* | 1.022 | -0.256 |
| *female:single-female:married* | 0.842 | -0.512 |
| *female:single-male:single* | -0.18 | -0.955 |
#+CAPTION: Table continues below
| | Upper Bound | P value |
|-----------------------------------------------------+---------------+-----------|
| *female:in a relationship-male:in a relationship* | 0.749 | /1/ |
| *male:married-male:in a relationship* | 1.103 | /1/ |
| *female:married-male:in a relationship* | 0.722 | /0.801/ |
| *male:single-male:in a relationship* | 1.119 | /0.412/ |
| *female:single-male:in a relationship* | 1.074 | /0.938/ |
| *male:married-female:in a relationship* | 1.148 | /1/ |
| *female:married-female:in a relationship* | 0.764 | /0.83/ |
| *male:single-female:in a relationship* | 1.184 | /0.461/ |
| *female:single-female:in a relationship* | 1.132 | /0.938/ |
| *female:married-male:married* | 1.097 | /0.946/ |
| *male:single-male:married* | 1.67 | /0.794/ |
| *female:single-male:married* | 1.575 | /0.971/ |
| *male:single-female:married* | 2.3 | /0.201/ |
| *female:single-female:married* | 2.196 | /0.481/ |
| *female:single-male:single* | 0.594 | /0.986/ |
There are no categories which differ significantly here.
***** Plot
Below you can see the result of the post hoc test on a plot.
[[plots/ANOVA-8-hires.png][[[plots/ANOVA-8.png]]]]
--------------
This report was generated with [[http://www.r-project.org/][R]] (3.0.1)
and [[https://rapporter.github.io/rapport/][rapport]] (0.51) in /3.431/ sec on
x86\_64-unknown-linux-gnu platform.
[[images/logo.png]]