THESISDISSERTATIONWS Telegram 978
I here explain different types of contrasts in repeated measures ANOVA. These are available in SPSS and R.


1. Polynomial Contrasts

Purpose: Test for linear, quadratic, cubic, etc., trends in the means across the repeated measures.

Use Case: When the levels of the within-subject factor are ordered (e.g., time points or doses).

Example: If you measure performance at 3 time points (T1, T2, T3), a linear contrast tests if the mean increases or decreases steadily, while a quadratic contrast tests for a curve (e.g., increase then decrease).
×××××××××××××××××××××××××
2. Deviation Contrasts

Purpose: Compare each level of the within-subject factor to the overall mean of all levels.

Use Case: When you want to know whether a particular condition differs significantly from the average of all conditions.

Example: Compare each teaching method (A, B, C) to the average effect across all three methods.
×××××××××××××××××××××××××
3. Simple Contrasts

Purpose: Compare each level of the within-subject factor to a reference level (usually the first or last).

Use Case: When you have a control or baseline condition and want to compare each other condition to it.

Example: Compare scores at Week 2 and Week 3 to Week 1 (baseline).
××××××××××××××××××××××××××
4. Repeated Contrasts

Purpose: Compare each level of the within-subject factor to the previous level.

Use Case: To test sequential changes (e.g., from one time point to the next).

Example: Compare performance at Week 2 to Week 1, then Week 3 to Week 2.
××××××××××××××××××××××××××
5. Helmert Contrasts

Purpose: Compare each level of the factor to the mean of subsequent levels.

Use Case: To examine whether early levels differ from the average of what comes next.

Example: Compare Week 1 to the average of Week 2 and Week 3; then compare Week 2 to Week 3.
×××××××××××××××××××××××××
6. Difference Contrasts

Purpose: Compare each level to the mean of preceding levels.

Use Case: The reverse of Helmert; used when later levels are to be compared to previous ones.

Example: Compare Week 3 to the average of Week 1 and Week 2.
××××××××××××××××××××××××××
Each should be based on your research questions and your research goal, as I summarised below:

For trends across time → Polynomial or Repeated

To compare to a control → Simple

To compare sequentially → Repeated

To compare each to average → Deviation

To test theoretical contrasts → Use Custom Contrasts (manually specify contrast weights)



tgoop.com/thesisdissertationws/978
Create:
Last Update:

I here explain different types of contrasts in repeated measures ANOVA. These are available in SPSS and R.


1. Polynomial Contrasts

Purpose: Test for linear, quadratic, cubic, etc., trends in the means across the repeated measures.

Use Case: When the levels of the within-subject factor are ordered (e.g., time points or doses).

Example: If you measure performance at 3 time points (T1, T2, T3), a linear contrast tests if the mean increases or decreases steadily, while a quadratic contrast tests for a curve (e.g., increase then decrease).
×××××××××××××××××××××××××
2. Deviation Contrasts

Purpose: Compare each level of the within-subject factor to the overall mean of all levels.

Use Case: When you want to know whether a particular condition differs significantly from the average of all conditions.

Example: Compare each teaching method (A, B, C) to the average effect across all three methods.
×××××××××××××××××××××××××
3. Simple Contrasts

Purpose: Compare each level of the within-subject factor to a reference level (usually the first or last).

Use Case: When you have a control or baseline condition and want to compare each other condition to it.

Example: Compare scores at Week 2 and Week 3 to Week 1 (baseline).
××××××××××××××××××××××××××
4. Repeated Contrasts

Purpose: Compare each level of the within-subject factor to the previous level.

Use Case: To test sequential changes (e.g., from one time point to the next).

Example: Compare performance at Week 2 to Week 1, then Week 3 to Week 2.
××××××××××××××××××××××××××
5. Helmert Contrasts

Purpose: Compare each level of the factor to the mean of subsequent levels.

Use Case: To examine whether early levels differ from the average of what comes next.

Example: Compare Week 1 to the average of Week 2 and Week 3; then compare Week 2 to Week 3.
×××××××××××××××××××××××××
6. Difference Contrasts

Purpose: Compare each level to the mean of preceding levels.

Use Case: The reverse of Helmert; used when later levels are to be compared to previous ones.

Example: Compare Week 3 to the average of Week 1 and Week 2.
××××××××××××××××××××××××××
Each should be based on your research questions and your research goal, as I summarised below:

For trends across time → Polynomial or Repeated

To compare to a control → Simple

To compare sequentially → Repeated

To compare each to average → Deviation

To test theoretical contrasts → Use Custom Contrasts (manually specify contrast weights)

BY Research Methods in AL


Share with your friend now:
tgoop.com/thesisdissertationws/978

View MORE
Open in Telegram


Telegram News

Date: |

With the “Bear Market Screaming Therapy Group,” we’ve now transcended language. The optimal dimension of the avatar on Telegram is 512px by 512px, and it’s recommended to use PNG format to deliver an unpixelated avatar. 2How to set up a Telegram channel? (A step-by-step tutorial) To delete a channel with over 1,000 subscribers, you need to contact user support A new window will come up. Enter your channel name and bio. (See the character limits above.) Click “Create.”
from us


Telegram Research Methods in AL
FROM American