Podcast
Questions and Answers
What is the primary goal of increasing the power of ANOVA?
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.
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?
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.
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.
What does the assumption of normality in dependent groups ANOVA primarily ensure?
What does the assumption of normality in dependent groups ANOVA primarily ensure?
Circularity, an assumption underlying dependent groups ANOVA, is primarily assessed using the Kolmogorov-Smirnov test.
Circularity, an assumption underlying dependent groups ANOVA, is primarily assessed using the Kolmogorov-Smirnov test.
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.
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.
In the context of ANOVA, what is the primary distinction between 'blocks' and 'subjects'?
In the context of ANOVA, what is the primary distinction between 'blocks' and 'subjects'?
The F-ratio for blocks is calculated to determine the extent to which the matching process was successful in reducing random error.
The F-ratio for blocks is calculated to determine the extent to which the matching process was successful in reducing random error.
State the formula for eta-squared ($η^2$) in the context of ANOVA.
State the formula for eta-squared ($η^2$) in the context of ANOVA.
If a significant F-ratio is observed in an ANOVA, what does this generally indicate?
If a significant F-ratio is observed in an ANOVA, what does this generally indicate?
In ANOVA, post-hoc tests are used to determine the magnitude of the overall effect, indicated by the eta-squared value.
In ANOVA, post-hoc tests are used to determine the magnitude of the overall effect, indicated by the eta-squared value.
In a computational example comparing four groups with 15 individuals each, which test should be used to analyze statistically if the participants were matched?
In a computational example comparing four groups with 15 individuals each, which test should be used to analyze statistically if the participants were matched?
If an independent groups ANOVA is used when the data are matched, it may result in an ______ of the subject variance.
If an independent groups ANOVA is used when the data are matched, it may result in an ______ of the subject variance.
If the assumptions of normality and homogeneity of variance are violated, what is the general advice?
If the assumptions of normality and homogeneity of variance are violated, what is the general advice?
Match each term with its correct description in the context of dependent groups ANOVA:
Match each term with its correct description in the context of dependent groups ANOVA:
In ANOVA, what does the term 'degrees of freedom' refer to?
In ANOVA, what does the term 'degrees of freedom' refer to?
In a dependent groups ANOVA, the degrees of freedom for the treatment effect are calculated differently than those in an independent groups ANOVA.
In a dependent groups ANOVA, the degrees of freedom for the treatment effect are calculated differently than those in an independent groups ANOVA.
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 ______ ($MS_E$).
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 ______ ($MS_E$).
How do you calculate the degrees of freedom for blocks/subjects ($df_B$)?
How do you calculate the degrees of freedom for blocks/subjects ($df_B$)?
Which of the following is the formula for degrees of freedom for unsystematic error in a dependent groups ANOVA design?
Which of the following is the formula for degrees of freedom for unsystematic error in a dependent groups ANOVA design?
Express the formula for sum of squares for error ($SS_E$) in a dependent groups ANOVA.
Express the formula for sum of squares for error ($SS_E$) in a dependent groups ANOVA.
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.
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.
In an ANOVA summary table, the formula used to calculate the Mean Square ($MS$) is $SS$ divided by ______.
In an ANOVA summary table, the formula used to calculate the Mean Square ($MS$) is $SS$ divided by ______.
What does a significant difference found through post hoc testing in the context of ANOVA indicate?
What does a significant difference found through post hoc testing in the context of ANOVA indicate?
When there is a treatment effect the mean D is not different from all of the other means.
When there is a treatment effect the mean D is not different from all of the other means.
In Tukey's HSD, what does $'v'$ represent in $w = q(k,v)\sqrt{MSE/\bar{n}} $?
In Tukey's HSD, what does $'v'$ represent in $w = q(k,v)\sqrt{MSE/\bar{n}} $?
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?
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?
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.
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.
Step 2 of conducting steps to determine if you should reject the null hypothesis requires checking assumptions, one of these assumptions is ______.
Step 2 of conducting steps to determine if you should reject the null hypothesis requires checking assumptions, one of these assumptions is ______.
What does 'k' represent when calculating degrees of freedom?
What does 'k' represent when calculating degrees of freedom?
In ANOVA, after obtaining a significant effect, follow-up tests such as Tukey's HSD are unnecessary as the overall effect is already known.
In ANOVA, after obtaining a significant effect, follow-up tests such as Tukey's HSD are unnecessary as the overall effect is already known.
How do you define a hypothesis statement?
How do you define a hypothesis statement?
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.
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.
Calculating the denominator degrees of freedom, why do the researchers drop down to the next lowest df estimate?
Calculating the denominator degrees of freedom, why do the researchers drop down to the next lowest df estimate?
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.
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.
If a researcher decides to use repeated measures, what advantage can this decision have?
If a researcher decides to use repeated measures, what advantage can this decision have?
State the steps one would take to run a computational example to determine if you should reject that null hypothesis.
State the steps one would take to run a computational example to determine if you should reject that null hypothesis.
A dependent groups ANOVA would not apply if the participants were well matched.
A dependent groups ANOVA would not apply if the participants were well matched.
In the hypothesis statement $Ha$ denotes at least one pair of ______ differ.
In the hypothesis statement $Ha$ denotes at least one pair of ______ differ.
What are you looking at when looking for circularity?
What are you looking at when looking for circularity?
Flashcards
Dependent Groups ANOVA
Dependent Groups ANOVA
A statistical test used to compare the means of two or more dependent groups.
Variance Partitioning
Variance Partitioning
The process of dividing the total variance in a data set into different sources of variation.
F-ratio
F-ratio
A ratio of the variance due to the treatment effect to the variance due to error.
Increasing Power of ANOVA
Increasing Power of ANOVA
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Independent Random Sampling
Independent Random Sampling
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Normality Assumption
Normality Assumption
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Circularity of Variance/Covariance Matrix
Circularity of Variance/Covariance Matrix
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Sum of Squares for Treatment
Sum of Squares for Treatment
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Sum of Squares for Error
Sum of Squares for Error
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Sum of Squares for Blocks/Subjects
Sum of Squares for Blocks/Subjects
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Sum of Squares for Unsystematic Error
Sum of Squares for Unsystematic Error
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Degrees of Freedom
Degrees of Freedom
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ANOVA Summary Table
ANOVA Summary Table
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Eta-square
Eta-square
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Pairwise Comparisons
Pairwise Comparisons
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Null Hypothesis
Null Hypothesis
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Alternative Hypothesis
Alternative Hypothesis
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Choose Test: Independent One-Way ANOVA
Choose Test: Independent One-Way ANOVA
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Choose Test: Dependent Groups One-Way ANOVA
Choose Test: Dependent Groups One-Way ANOVA
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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 (x̄k - x̄g )^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 (x̄b - x̄g )^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 (x̄k - x̄g )^2
- Sum of squares for blocks / subjects is: Σ nb (x̄b - x̄g )^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 (x̄k - x̄g )^2, df = k-1, MS = SST/dfT , F = MST/ MSE
- For blocks: SS = Σ nb (x̄b - x̄g )^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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