"A learned,
detached examination of the well springs of modern psychology." Jude Dougherty |
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"Would you
like to investigate causality within psychology, as a scientist might rather than a statistician?" Paul Barrett |
OOM Instructional Videos...
Below you will find a variety of instructional videos for the Observation Oriented Modeling (OOM) software. A good place to start is with the Introductory Videos which explain the ideas behind the software and provide an overview of the program's structure and functionality. In separate tables below these two introductory videos you will find more specific videos organized into two categories: General Videos and Specific OOM Analysis Videos. You will also find a table of OOM Equivalent Analyses for Traditional Statistical Procedures such as t-tests, chi-squares, and ANOVAs. This latter table will help you to see how traditional statistical analyses can be replaced by OOM analyses.
Last Update: March 3rd, 2022; OOM Website
Introductory Videos
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Video Title | Description |
OOM: What is it? How does it work? Why should I use it? | As the title indicates, this video explains
the general theory and philosophy guiding OOM. It also briefly explains how OOM
differs from traditional statistics and shows a number of example analyses.
(~15 minutes in length) |
Getting beyond NHST (the p-value) | Why should psychologists and other social scientists abandon the common p-value (NHST)? Briefly, NHST is used to draw inferences to population parameters and requires random sampling to be successful; yet, most psychologists and social scientists do not even attempt to draw random samples. They are therefore clearly seeking a different inference, and in this video we argue it is the Inference to Best Explanation that is being sought. OOM provides the means for seeking such an inference. (~10 minutes in length) |
A first look at the OOM software | Provides a brief preview of the software, showing how analyses are focused on patterns and persons (observations) rather than upon means, standard deviations, and variances. |
General Videos
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Video Title | Description |
Installation & Overview | Explains how OOM installs onto your PC. The User's Manual installs with the program in Word and Adobe Acrobat format, and a large number of OOM example data files install automatically as well. This video also provides a general overview of the OOM software's structure and functionality. (~5 minutes) |
Running OOM on a Mac | Demonstrates how to use Winebottler, a free program, to run OOM on a Macintosh computer. There is no separate Mac version of OOM, so the program must be run through a PC emulator such as Winebottler. (~ 9 minutes) |
Data Edit Window Toolbar | Explains the functions of the various tool buttons on the toolbar of the Data Edit window. (~ 5 minutes) |
Data Edit Window Sub-Toolbar | Explains the functions of the various tool buttons on the sub-toolbar of the Data Edit window. (~ 5 minutes) |
Text Output Window | Describes the different features in the Text Output window, including how fonts can be changes and how the number of decimals in numeric output printed can be changed. (~ 6 minutes) |
Graphics Output Window | Describes how graphs are created, viewed, edited, and saved in OOM. Also demonstrates how graphs can be exported to MS Powerpoint for editing. (~ 6 minutes) |
Data
Entry #1 Data Entry #2 Data Entry #3 |
These videos demonstrate how data are entered and labeled in the OOM software. Labeling units of observation is very important in OOM as this is tantamount to determining the Deep Structure of the data. Most analyses are based on the Deep Structures of the data. These videos also include descriptions of the Define Orderings window and the Auto Generate options for defining units of observation. (~4 to 8 minutes in length) |
Deep Structure | Explains the concept of Deep Structure in OOM and gives several examples. (~ 5 minutes) |
Importing from Excel Importing from SPSS |
Demonstrates how data can be imported from an Excel spreadsheet or from an SPSS file. Each video is ~6 minutes in length. |
Generate Data | Shows how data from proportions or frequencies (e.g., as reported in a contingency table) can be created quickly using the Generate Observations option. |
Multigram Options Editing Multigrams |
The first video describes the various display features for multigrams in the OOM software. The second video shows how multigrams can be exported as Windows Metafiles and then edited, in detail, in other programs such as Powerpoint and Word. |
Specific OOM Analysis Videos
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OOM Analysis Video | Analysis Description | Related Materials |
Build/Test Model
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The Build/Test Model option allows you to explore the relationships between two or more orderings (variables). For example, how are aspirin ingestion and the common cold related, or how is relationship investment and satisfaction related to relationship commitment? The relationships are not assumed to be linear, and the analysis uses a Bayesian-like classifier to determine how many individuals fit the discovered pattern (if any) within the data. The Build/Test option thus offers post hoc methods for identifying patterns; in other words, you are not required to specify an expected pattern prior to analysis. The primary visual tool is a multigram, a number of examples which can be viewed here. | |
Ordinal Analysis: Concatenated Orderings
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This analysis allows you to examine ordinal
differences across two or more orderings. This may be useful, for example,
in analyzing changes in quantities over time, such as with a pre- and
post-test study design. Normally, you will specify the predicted ordinal
pattern before running the analysis. Here is an example defined pattern in
which quantities are expected to decrease from pre-test to post-test:
Pre-Test |
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Ordinal Analysis: Crossed Orderings | This analysis allows you to examine ordinal
differences across two or more groups of individuals. For example, suppose a
memory researcher assigns participants to two experimental (A and B) and one
control group. The outcome variable is number of words recalled from a
memory task, and the researcher expects group A to recall more words than
group B, and group B to recall more words than the control group. The
expected ordinal pattern across the three groups is therefore: A > B >
Control. Here is pattern in visual form: A B Control + O O Highest O + O O O + Lowest (+ indicates expected ordinal pattern) |
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Pattern Analysis: Concatenated Orderings | This analysis allows you to test a specific
pattern of observations across several orderings. For example, you might
consider binge drinkers to self-report relatively high levels of
extraversion and agreeableness and relatively low levels of
conscientiousness. If the personality scale is divided into four quarters,
then the expected pattern may appear as follows: E A C Q4 + + O Q3 + + O Q2 O O + Q1 O O + (+ indicates expected locations of observations) |
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Pattern Analysis: Crossed Orderings | This analysis allows you to test a specific
pattern of observations within a two-dimensional matrix. This may be useful,
for example, in comparing two groups on a rating scale. You must specify the
predicted pattern before running the analysis. Here is an example
defined pattern: Scale Rating 1 2 3 4 5 6 + + + O O O Group 1 O O O + + + Group 2 (+ indicates expected rating) |
Grice, 2015 publication demonstrating this analysis. |
Efficient Cause: Blocked Orderings | Efficient causes are those ordered in time,
as with the classic S --> R concept in psychology. The Blocked Orderings
efficient cause analysis
can be used to analyze data that are blocked across time, like those found
in an ABAB research design. For example, a behavioral clinical psychologist
might examine the causal efficacy of a treatment program by assessing the
number of disruptive behaviors for each child in a classroom. She assesses
five time points within each of four blocks of trials in an ABAB design: 1)
no treatment, 2) treatment, 3) no treatment, and 4) treatment. She might
expect the following ordinal pattern of disruptive behaviors across the four
trials:
A Each child's data can also be examined and assessed with this analysis. |
Parker and colleagues review methods similar to those in OOM: |