Dependent Groups ANOVA

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Questions and Answers

What is the primary goal of increasing the power of ANOVA?

  • Increase the size of the F-ratio (correct)
  • Decrease the size of the F-ratio
  • Minimize the treatment effect
  • Maximize the error term

Increasing the magnitude of the treatment effect is generally a practical approach to increasing the power of ANOVA.

False (B)

Which of the following actions can increase the power within an ANOVA test?

  • Decreasing the treatment effect
  • Increasing the error term's magnitude
  • Better control of error (correct)
  • Minimizing control of error

In dependent groups ANOVA, 'independent random sampling' implies that the sampling of any given participant within the data is dependent on the presence of any other participant within the data.

<p>False (B)</p> Signup and view all the answers

What does the assumption of normality in dependent groups ANOVA primarily ensure?

<p>Does not have a large effect on Type I/II error (B)</p> Signup and view all the answers

Circularity, an assumption underlying dependent groups ANOVA, is primarily assessed using the Kolmogorov-Smirnov test.

<p>False (B)</p> Signup and view all the answers

In dependent groups ANOVA, the unsystematic error term of the independent groups ANOVA has been partitioned into ______ sources of error, and unsystematic sources of error.

<p>systematic</p> Signup and view all the answers

In the context of ANOVA, what is the primary distinction between 'blocks' and 'subjects'?

<p>'Blocks' are used in randomized block designs, while 'subjects' are used in repeated measures designs. (B)</p> Signup and view all the answers

The F-ratio for blocks is calculated to determine the extent to which the matching process was successful in reducing random error.

<p>False (B)</p> Signup and view all the answers

State the formula for eta-squared ($η^2$) in the context of ANOVA.

<p>$η^2 = \frac{SS_{Treatment}}{SS_{Total}}$</p> Signup and view all the answers

If a significant F-ratio is observed in an ANOVA, what does this generally indicate?

<p>At least one pair of group means is significantly different. (D)</p> Signup and view all the answers

In ANOVA, post-hoc tests are used to determine the magnitude of the overall effect, indicated by the eta-squared value.

<p>False (B)</p> Signup and view all the answers

In a computational example comparing four groups with 15 individuals each, which test should be used to analyze statistically if the participants were matched?

<p>Dependent groups ANOVA (B)</p> Signup and view all the answers

If an independent groups ANOVA is used when the data are matched, it may result in an ______ of the subject variance.

<p>overestimation</p> Signup and view all the answers

If the assumptions of normality and homogeneity of variance are violated, what is the general advice?

<p>Use a non-parametric alternative. (C)</p> Signup and view all the answers

Match each term with its correct description in the context of dependent groups ANOVA:

<p>Systematic Error = Error that can be attributed to known or controlled sources. Unsystematic Error = Error that is random and cannot be attributed to specific sources. Treatment Effect = The impact of the independent variable on the dependent variable. F-Ratio = The ratio of variance between groups to variance within groups.</p> Signup and view all the answers

In ANOVA, what does the term 'degrees of freedom' refer to?

<p>The number of scores that are free to vary (B)</p> Signup and view all the answers

In a dependent groups ANOVA, the degrees of freedom for the treatment effect are calculated differently than those in an independent groups ANOVA.

<p>False (B)</p> Signup and view all the answers

In an ANOVA summary table, the F statistic is calculated as the ratio of the Mean Square for Treatment ($MS_T$) to the Mean Square for ______ ($MS_E$).

<p>Error</p> Signup and view all the answers

How do you calculate the degrees of freedom for blocks/subjects ($df_B$)?

<p>$df_B = b - 1$ (B)</p> Signup and view all the answers

Which of the following is the formula for degrees of freedom for unsystematic error in a dependent groups ANOVA design?

<p>$(k - 1)(b - 1)$ (D)</p> Signup and view all the answers

Express the formula for sum of squares for error ($SS_E$) in a dependent groups ANOVA.

<p>$SS_{Total} - SS_T - SS_{Blocks}$</p> Signup and view all the answers

A non-significant F-ratio for the blocks effect in a repeated measures ANOVA suggests that one should proceed with the analysis after removing the systematic error.

<p>False (B)</p> Signup and view all the answers

In an ANOVA summary table, the formula used to calculate the Mean Square ($MS$) is $SS$ divided by ______.

<p>df</p> Signup and view all the answers

What does a significant difference found through post hoc testing in the context of ANOVA indicate?

<p>At least one group mean is significantly different from another group mean. (B)</p> Signup and view all the answers

When there is a treatment effect the mean D is not different from all of the other means.

<p>False (B)</p> Signup and view all the answers

In Tukey's HSD, what does $'v'$ represent in $w = q(k,v)\sqrt{MSE/\bar{n}} $?

<p>Degrees of freedom for the mean square error (A)</p> Signup and view all the answers

A researcher conducts a study using a dependent groups ANOVA and calculates the $F$ obt. of 9.36. If the $F$ critical is 2.839, what decision should the researcher make regarding the null hypothesis?

<p>Reject the null hypothesis (B)</p> Signup and view all the answers

A researcher conducts a study using a dependent groups ANOVA, one benefit of this design is that it tends to be less powerful due to better matching.

<p>False (B)</p> Signup and view all the answers

Step 2 of conducting steps to determine if you should reject the null hypothesis requires checking assumptions, one of these assumptions is ______.

<p>circularity</p> Signup and view all the answers

What does 'k' represent when calculating degrees of freedom?

<p>number of treatments (D)</p> Signup and view all the answers

In ANOVA, after obtaining a significant effect, follow-up tests such as Tukey's HSD are unnecessary as the overall effect is already known.

<p>False (B)</p> Signup and view all the answers

How do you define a hypothesis statement?

<p>Hypothesis statements express the intent of researchers expectations. It establishes the null and alternative.</p> Signup and view all the answers

In repeated measures ANOVA, the $SS_{Total}$ represents the total variability in the data. It can be partitioned into the sum of squares due to the treatment effect, the sum of squares due to ________, and the sum of squares due to error.

<p>Block</p> Signup and view all the answers

Calculating the denominator degrees of freedom, why do the researchers drop down to the next lowest df estimate?

<p>to ensure the analysis is valid (C)</p> Signup and view all the answers

By proceeding with the same data through a dependent groups ANOVA can we can better control errors to see if we can have an impact on the subjects.

<p>True (A)</p> Signup and view all the answers

If a researcher decides to use repeated measures, what advantage can this decision have?

<p>There is better matching (D)</p> Signup and view all the answers

State the steps one would take to run a computational example to determine if you should reject that null hypothesis.

<ol> <li>Create a hypothesis statement, 2. Choose a test, 3. Check the assumptions, 4. Define the rejection region, 5. Calculate the sum of squares, 6. run an ANOVA summary table, 7. Make a conscious decision.</li> </ol> Signup and view all the answers

A dependent groups ANOVA would not apply if the participants were well matched.

<p>False (B)</p> Signup and view all the answers

In the hypothesis statement $Ha$ denotes at least one pair of ______ differ.

<p>means</p> Signup and view all the answers

What are you looking at when looking for circularity?

<p>homogeneity (A)</p> Signup and view all the answers

Flashcards

Dependent Groups ANOVA

A statistical test used to compare the means of two or more dependent groups.

Variance Partitioning

The process of dividing the total variance in a data set into different sources of variation.

F-ratio

A ratio of the variance due to the treatment effect to the variance due to error.

Increasing Power of ANOVA

Improving the statistical test's ability to detect a true effect.

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Independent Random Sampling

The premise that data points are selected independently and randomly from the population.

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Normality Assumption

Populations from which samples are taken are normally distributed.

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Circularity of Variance/Covariance Matrix

Variance of the difference between any two treatment groups equals the variance of the difference between any other two.

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Sum of Squares for Treatment

Represents the variability of the treatment effect, unaffected by partitioning in dependent groups ANOVA.

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Sum of Squares for Error

Systematic sources of error are separated from unsystematic sources of error.

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Sum of Squares for Blocks/Subjects

Variability due to individual differences among subjects or blocks.

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Sum of Squares for Unsystematic Error

The variation in the data that is not explained by the treatment or subject differences.

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Degrees of Freedom

The number of independent pieces of information used to calculate a statistic.

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ANOVA Summary Table

A table summarizing the results, including sources of variation, sums of squares, degrees of freedom, mean squares, and F-ratios.

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Eta-square

A measure of the proportion of variance in the dependent variable that is explained by the independent variable.

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Pairwise Comparisons

Statistical tests to determine which groups differ significantly from each other.

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Null Hypothesis

A statement that there is no significant difference between the means of the groups being compared.

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Alternative Hypothesis

A statement that there is a significant difference between the means of the groups being compared.

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Choose Test: Independent One-Way ANOVA

A statistical test for comparing 4 independent groups.

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Choose Test: Dependent Groups One-Way ANOVA

A statistical test for comparing 4 matched groups.

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Study Notes

Dependent Groups ANOVA

  • Dependent Groups ANOVA is the topic

Variance Partitioning

  • Variance partitioning is being reviewed
  • Variance total (σ total^2) can be partitioned into variance treatment (σ treatment^2) and variance error (σ error^2)
  • F is calculated as: F = σ treatment^2 / σ error^2
  • Systematic variance is due to treatment effect
  • Unsystematic variance is error

Increasing the Power of ANOVA

  • Increasing the F-ratio size increases the power of ANOVA
  • This can be achieved by:
    • Increasing the magnitude of the treatment effect, although is not generally practical
    • Decreasing the magnitude of the error term
  • Better control of error increases power within ANOVA

Assumptions Underlying Dependent Groups ANOVA

  • ANOVA is subject to certain assumptions: including, but not limited to the following.
  • Should sampling be performed randomly and independently
  • Participants within each level need to be representative of the population from which they are drawn
  • Sampling of any given participant within the data is not dependent on the presence of any other participant within the data
  • Assumption does not include any matching variables
  • This randomness is considered critical
  • Population samples must be normally distributed
  • Normality does not largely effect the Type I/II error of a dependent groups ANOVA
  • There is circularity of the variance/covariance matrix
  • Variance of difference between any two treatment groups is equal to variance of the difference between any other two
  • This is typically tested using Mauchly’s test of sphericity

Sum of Squares for Treatment

  • Sum of squares for the treatment effect remains the same
  • Variance of the treatment effect has not been partitioned further
  • This sum is calculated by : Σ nk (xÌ„k - xÌ„g )^2

Sum of Squares for Error

  • Sum of squares for the error term is different in a dependent groups ANOVA versus independent groups
  • The unsystematic error term of the independent groups ANOVA is partitioned into systematic and unsystematic sources of error

Systematic and Unsystematic Error

  • New sources of variability are either blocks or subjects
  • This depends on whether the design is a randomized blocks design, or a repeated measures design
  • This sum of squares is calculated by: Σ nb (xÌ„b - xÌ„g )^2

Sum of Squares for Error

  • The sum of squares for unsystematic error is everything left over
  • SSTotal = SST + SSBlock + SSError
  • Two terms (SSBlock + SSError), represents the error term for the independent samples ANOVA

Summary of Sum of Squares

  • Sum of squares for treatment is: Σ nk (xÌ„k - xÌ„g )^2
  • Sum of squares for blocks / subjects is: Σ nb (xÌ„b - xÌ„g )^2
  • Sum of squares for error is: SSTotal - SST - SSBlocks

Degrees of Freedom

  • Degrees of freedom for treatment effect remain unchanged
  • Calculated by: dfT = k − 1
  • Degrees of freedom for blocks / subjects computed in same way as treatment effect
  • Calculated by: dfB = b − 1
  • Degrees of freedom for unsystematic error
  • Calculated by : (k – 1)(b − 1)

ANOVA Summary Table

  • Table includes:
  • Source
  • SS (sum of squares)
  • df (degrees of freedom)
  • MS (mean squares)
  • F (F statistic)
  • Source is either: Treatment, Blocks, or Error
  • For treatment: SS = Σ nk (xÌ„k - xÌ„g )^2, df = k-1, MS = SST/dfT , F = MST/ MSE
  • For blocks: SS = Σ nb (xÌ„b - xÌ„g )^2, df = b-1, MS = SSB/dfB
  • For error: SS = SSTotal - SST – SSB, df = (k-1)(b − 1), MS = SSE/dfE

Is there an F-ratio for Blocks?

  • Yes and no
  • The F-ratio for blocks tests the extent to which matching was successful in pulling out systematic variability
  • NOTE: a non-significant F-ratio for the blocks effect does NOT suggest that you should run the analysis without removing systematic error

Eta-square

  • Same calculation as independent groups ANOVA (SSTreatment/SSTotal)
  • n^2 = SSTreatment / SSTotal

Pairwise Comparisons

  • As with independent groups ANOVA, a significant F-ratio indicates a difference between groups, but not where this difference lies
  • Can use the same post hoc tests as used within independent groups analysis

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