**Efficient Cause Analysis - Paired Orderings**

**Generic Questions: **Do two variables (orderings) change
consistently over time or across multiple occasions? Do changes in one ordering
follow changes in another ordering in time (a lagged effect over time). More
generally, do changes in one ordering cause changes in the second ordering?

**Data Type**: Two or more qualitative or quantitative orderings (variables).
Longitudinal / repeated measures /
within-subjects / dependent observations

**
Hypotheses**: The pattern of change in one ordering across time or occasions
will match (or be opposite of) the pattern in a second ordering

Traditional analogs

Summary

**Software Access**: The *Efficient
Cause Analysis -- Paired Orderings* procedure can be found by selecting "*Analyses -->
Efficient Cause Analysis --> Paired Orderings*" from the Main Menu. The procedure window
appears as:

**Videos and Files:** The following videos
and files describe the procedure and its various
options. Be sure to set the video quality to High Definition (1080p) if the
browser does not automatically do so. If you wish to follow along with the
analyses on your own computer, download and open the data set(s) linked at the
bottom of this page.

**Definitions**(a list of definitions commonly used in the OOM software and in observation oriented modeling):**Introduction**(a brief introduction to the procedure that describes how the analysis is conducted):**Specific Options**(the Analyze, Missing Values, Randomization Test, etc. options in the analysis and options window above are explained and demonstrated):- Examine Patterns button
- Ordinal Patterns button
- Analyze: Deep Structures or Numbers (Ordinal)
- Reflect Units/Values
- Ordinal Classifications: Full or Adjacent
- Missing Values: Omit or Include
- Classification Imprecision
- Effect Lag (see also the "Lagging the Effect in time" link above)
- Randomization Test (with four sub-options):
- Introduction/Overview of Randomization Test option
- Discussion of different randomization options
- Save Randomization Results
- Choosing a randomization procedure (a Powerpoint hand-out explaining what to consider when choosing between the two sub-options)

- Individual Results
- Individual Classifications
- Append, Save Individual Results

**Comparing Two PCCs**(a demonstration of how a chance-value can be determined for the difference between two PCCs):- Chance-value for difference between two PCCs

**Planning Sample Size**(based on the chance-value)- Description of steps in the procedure to determine sample size (review the steps on this handout before watching the videos linked below)
- Creating a Data Set
- Running the Analysis and Examining Randomization Results Distribution
- Comparison of planned sample size and actual sample size

**Reporting Results**

- Example APA write-ups for the
*Efficient Cause -- Paired Orderings*procedure. - See our Observation Oriented Modeling: Going Beyond "Is it all a Matter of Chance" paper. The OOM analyses are re-analyses of data originally reported by Shoda, Wilson, et al., 2012.

**Data**

**Data Sets**(used in videos above)