ANCOVA - overview
This page offers structured overviews of one or more selected methods. Add additional methods for comparisons (max. of 3) by clicking on the dropdown button in the right-hand column. To practice with a specific method click the button at the bottom row of the table
ANCOVA | Cochran's Q test | Repeated measures ANCOVA |
You cannot compare more than 3 methods |
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Independent variables | Independent/grouping variable | Independent variable | |
One or more categorical with independent groups, and one or more quantitative control variables of interval or ratio level (covariates) | One within subject factor ($\geq 2$ related groups) | One or more within subjects factors (related groups), one or more quantitative control variables of interval or ratio level (covariates), and possibly one or more between subjects factors (independent groups) | |
Dependent variable | Dependent variable | Dependent variables | |
One quantitative of interval or ratio level | One categorical with 2 independent groups | One quantitative of interval or ratio level | |
THIS TABLE IS YET TO BE COMPLETED | Null hypothesis | THIS TABLE IS YET TO BE COMPLETED | |
- | H0: $\pi_1 = \pi_2 = \ldots = \pi_I$
Here $\pi_1$ is the population proportion of 'successes' for group 1, $\pi_2$ is the population proportion of 'successes' for group 2, and $\pi_I$ is the population proportion of 'successes' for group $I.$ | - | |
n.a. | Alternative hypothesis | n.a. | |
- | H1: not all population proportions are equal | - | |
n.a. | Assumptions | n.a. | |
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n.a. | Test statistic | n.a. | |
- | If a failure is scored as 0 and a success is scored as 1:
$Q = k(k - 1) \dfrac{\sum_{groups} \Big (\mbox{group total} - \frac{\mbox{grand total}}{k} \Big)^2}{\sum_{blocks} \mbox{block total} \times (k - \mbox{block total})}$ Here $k$ is the number of related groups (usually the number of repeated measurements), a group total is the sum of the scores in a group, a block total is the sum of the scores in a block (usually a subject), and the grand total is the sum of all the scores. Before computing $Q$, first exclude blocks with equal scores in all $k$ groups. | - | |
n.a. | Sampling distribution of $Q$ if H0 were true | n.a. | |
- | If the number of blocks (usually the number of subjects) is large, approximately the chi-squared distribution with $k - 1$ degrees of freedom | - | |
n.a. | Significant? | n.a. | |
- | If the number of blocks is large, the table with critical $X^2$ values can be used. If we denote $X^2 = Q$:
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n.a. | Equivalent to | n.a. | |
- | Friedman test, with a categorical dependent variable consisting of two independent groups. | - | |
n.a. | Example context | n.a. | |
- | Subjects perform three different tasks, which they can either perform correctly or incorrectly. Is there a difference in task performance between the three different tasks? | - | |
n.a. | SPSS | n.a. | |
- | Analyze > Nonparametric Tests > Legacy Dialogs > K Related Samples...
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n.a. | Jamovi | n.a. | |
- | Jamovi does not have a specific option for the Cochran's Q test. However, you can do the Friedman test instead. The $p$ value resulting from this Friedman test is equivalent to the $p$ value that would have resulted from the Cochran's Q test. Go to:
ANOVA > Repeated Measures ANOVA - Friedman
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Practice questions | Practice questions | Practice questions | |