**Ordinal Analysis - Crossed Orderings**

**Generic Question: **Is there a meaningful difference
between two independent groups on an
ordering (variable)?

**Data Type**: One quantitative outcome ordering (variable), and at least one
categorical grouping ordering. Between-subjects /
between-groups / independent observations

**
Hypotheses**: Ordinal (e.g., Group

Traditional analogs

**Summary**: This analysis can be used when you wish to compare two or more
groups of persons on a quantitative ordering (variable). For instance, males and
females can be compared with regard to their height (a continuous quantity), or
Catholics and Protestants can be compared with regard to their number of daily
prayers (a discrete, countable quantity). Three or more groups can be compared
as well. This analysis can therefore be used instead of an independent samples
t-test or a oneway ANOVA. With regard to classic non-parametric statistical
tests, this analysis is most similar to the Mann-Whitney U test for independent
samples.

**Software Access**: The *Ordinal Analysis -- Crossed
Orderings* procedure can be found by selecting "*Analyses --> Ordinal
Analysis --> Crossed 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):- Classification Imprecision
- Missing Values: Omit or Include
- Analyze: Numbers or Deep Structures
- Randomize (with two sub-options):
- Randomize: All Observations
- Randomize: Deep Structures
- Choosing a randomization procedure (a Powerpoint hand-out explaining what to consider when choosing between the two sub-options)

- Pairwise Results (this video shows an example with three groups)
- Complete Results (this video shows an example with three groups)
- Separate by Ordering feature

**Comparing Two PCCs**(a demonstration of how a chance-value can be determined for the difference between two PCCs):**Post Hoc Pattern**(shows how to run the analysis in the event a predicted ordinal pattern is not available):**Planning Sample Size**(based on the chance-value)- Description of steps in the procedure to determine sample size (read this before watching the videos linked below)
- Creating a Data Set
- Running the Analysis
- Examining the Randomization Results Distribution

**Reporting Results**

- Example APA write-ups for the
*Ordinal Analysis -- Crossed Orderings*procedure. - See our
Persons as Effect Sizes paper. The second study reported in this paper
used the
*Ordinal Analysis - Crossed Orderings*procedure, sans the randomization test.

**Data**

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