tips:multiple_factors_interactions
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tips:multiple_factors_interactions [2021/10/22 14:44] – Wolfgang Viechtbauer | tips:multiple_factors_interactions [2022/08/03 11:35] – Wolfgang Viechtbauer | ||
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R^2 (amount of heterogeneity accounted for): 49.85% | R^2 (amount of heterogeneity accounted for): 49.85% | ||
- | Test for Residual Heterogeneity: | + | Test for Residual Heterogeneity: |
QE(df = 15) = 24.1362, p-val = 0.0628 | QE(df = 15) = 24.1362, p-val = 0.0628 | ||
- | Test of Moderators (coefficient(s) 2, | + | Test of Moderators (coefficient(s) 2,3,4): |
QM(df = 3) = 9.9698, p-val = 0.0188 | QM(df = 3) = 9.9698, p-val = 0.0188 | ||
Model Results: | Model Results: | ||
- | | + | |
intrcpt | intrcpt | ||
weekssome | weekssome | ||
weekshigh | weekshigh | ||
- | testeraware | + | testeraware |
--- | --- | ||
Line 109: | Line 109: | ||
We have also not yet tested whether there is a difference between levels '' | We have also not yet tested whether there is a difference between levels '' | ||
<code rsplus> | <code rsplus> | ||
- | anova(res.a1, | + | anova(res.a1, |
</ | </ | ||
<code output> | <code output> | ||
- | Hypothesis: | + | Hypothesis: |
1: weekssome - weekshigh = 0 | 1: weekssome - weekshigh = 0 | ||
Line 202: | Line 202: | ||
H^2 (unaccounted variability / sampling variability): | H^2 (unaccounted variability / sampling variability): | ||
- | Test for Residual Heterogeneity: | + | Test for Residual Heterogeneity: |
QE(df = 15) = 24.1362, p-val = 0.0628 | QE(df = 15) = 24.1362, p-val = 0.0628 | ||
- | Test of Moderators (coefficient(s) 1, | + | Test of Moderators (coefficient(s) 1,2,3,4): |
QM(df = 4) = 12.6719, p-val = 0.0130 | QM(df = 4) = 12.6719, p-val = 0.0130 | ||
Model Results: | Model Results: | ||
- | | + | |
weeksnone | weeksnone | ||
- | weekssome | + | weekssome |
- | weekshigh | + | weekshigh |
- | testeraware | + | testeraware |
--- | --- | ||
Line 250: | Line 250: | ||
R^2 (amount of heterogeneity accounted for): 0.00% | R^2 (amount of heterogeneity accounted for): 0.00% | ||
- | Test for Residual Heterogeneity: | + | Test for Residual Heterogeneity: |
QE(df = 13) = 23.4646, p-val = 0.0364 | QE(df = 13) = 23.4646, p-val = 0.0364 | ||
- | Test of Moderators (coefficient(s) 2, | + | Test of Moderators (coefficient(s) 2,3,4,5,6): |
QM(df = 5) = 9.3154, p-val = 0.0971 | QM(df = 5) = 9.3154, p-val = 0.0971 | ||
Model Results: | Model Results: | ||
- | | + | |
intrcpt | intrcpt | ||
- | weekssome | + | weekssome |
- | weekshigh | + | weekshigh |
- | testeraware | + | testeraware |
- | weekssome: | + | weekssome: |
- | weekshigh: | + | weekshigh: |
--- | --- | ||
Line 277: | Line 277: | ||
</ | </ | ||
<code output> | <code output> | ||
- | Test of Moderators (coefficient(s) 5,6): | + | Test of Moderators (coefficient(s) 5,6): |
QM(df = 2) = 0.8576, p-val = 0.6513 | QM(df = 2) = 0.8576, p-val = 0.6513 | ||
</ | </ | ||
Line 317: | Line 317: | ||
H^2 (unaccounted variability / sampling variability): | H^2 (unaccounted variability / sampling variability): | ||
- | Test for Residual Heterogeneity: | + | Test for Residual Heterogeneity: |
QE(df = 13) = 23.4646, p-val = 0.0364 | QE(df = 13) = 23.4646, p-val = 0.0364 | ||
- | Test of Moderators (coefficient(s) 1, | + | Test of Moderators (coefficient(s) 1, |
QM(df = 6) = 11.9111, p-val = 0.0640 | QM(df = 6) = 11.9111, p-val = 0.0640 | ||
Model Results: | Model Results: | ||
- | | + | |
weeksnone: | weeksnone: | ||
- | weekssome: | + | weekssome: |
- | weekshigh: | + | weekshigh: |
weeksnone: | weeksnone: | ||
- | weekssome: | + | weekssome: |
- | weekshigh: | + | weekshigh: |
--- | --- | ||
Line 339: | Line 339: | ||
Now, the table with the model results directly provides the estimated average effect for each factor level combination. It is now also quite easy to test particular factor level combinations against each other. For example, to test the difference between levels '' | Now, the table with the model results directly provides the estimated average effect for each factor level combination. It is now also quite easy to test particular factor level combinations against each other. For example, to test the difference between levels '' | ||
<code rsplus> | <code rsplus> | ||
- | anova(res.i2, | + | anova(res.i2, |
</ | </ | ||
<code output> | <code output> | ||
- | Hypothesis: | + | Hypothesis: |
1: weekssome: | 1: weekssome: | ||
Line 365: | Line 365: | ||
To test the same contrast within the '' | To test the same contrast within the '' | ||
<code rsplus> | <code rsplus> | ||
- | anova(res.i2, | + | anova(res.i2, |
</ | </ | ||
<code output> | <code output> | ||
- | Hypothesis: | + | Hypothesis: |
1: weekssome: | 1: weekssome: | ||
Line 400: | Line 400: | ||
Linear Hypotheses: | Linear Hypotheses: | ||
- | | + | |
- | some:blind - none:blind == 0 -0.15660 | + | some:blind - none:blind == 0 -0.15660 |
- | high:blind - none:blind == 0 -0.32675 | + | high:blind - none:blind == 0 -0.32675 |
- | none:aware - none:blind == 0 0.17592 | + | none:aware - none:blind == 0 0.17592 |
- | some:aware - none:blind == 0 -0.25818 | + | some:aware - none:blind == 0 -0.25818 |
- | high:aware - none:blind == 0 -0.41418 | + | high:aware - none:blind == 0 -0.41418 |
- | high:blind - some:blind == 0 -0.17015 | + | high:blind - some:blind == 0 -0.17015 |
- | none:aware - some:blind == 0 0.33252 | + | none:aware - some:blind == 0 0.33252 |
- | some:aware - some:blind == 0 -0.10158 | + | some:aware - some:blind == 0 -0.10158 |
- | high:aware - some:blind == 0 -0.25759 | + | high:aware - some:blind == 0 -0.25759 |
- | none:aware - high:blind == 0 0.50267 | + | none:aware - high:blind == 0 0.50267 |
- | some:aware - high:blind == 0 0.06857 | + | some:aware - high:blind == 0 0.06857 |
- | high:aware - high:blind == 0 -0.08744 | + | high:aware - high:blind == 0 -0.08744 |
- | some:aware - none:aware == 0 -0.43410 | + | some:aware - none:aware == 0 -0.43410 |
high:aware - none:aware == 0 -0.59010 | high:aware - none:aware == 0 -0.59010 | ||
high:aware - some:aware == 0 -0.15601 | high:aware - some:aware == 0 -0.15601 |
tips/multiple_factors_interactions.txt · Last modified: 2023/05/30 07:51 by Wolfgang Viechtbauer