his class is designed to provide participants a working knowledge of structural equation modeling and the LISREL program Students in Soc402 can most easily satisfy these requirements by selecting a pu

his class is designed to provide participants a working knowledge of structural equation

modeling and the LISREL program

Students in Soc402 can most easily satisfy these requirements by selecting a published

article that estimated a structural equation model, IF that article contains a covariance matrix (or

correlation matrix and standard deviations) for the modelled variables. The student’s model can be

a direct replication of the published model, and the student’s project can report about the things

they learned by doing the replication. The student’s selected article must be OK’d by me in the

first two weeks of class to ensure the article and model do not contain features that are too difficult

for a student project. If an article is used, a link to, or copy of, that article must be provided in the

final report. If you wish to use some other data set please talk to me after our first meeting.

The write-up of your project should be submitted electronically via canvas, and include comments

regarding:

1) the data set employed, the variables, and their coding -- plus the article or a link

2) the academic context of your model (e.g. was it: used by others?, a modification of a model

that had been used by others?, your own theory?). Only a very-brief context statement is

required and at least data-documenting references will be required. If the model corresponds

to “your own theory” this should be reported and no theory-reference would be required, but

a data-reference should be provided.

3) difficulties in model specification (if relevant)

4) a model diagram (a clear hand-drawn diagram of the final model is acceptable; un-

polished/rough diagram drafts may be included to assist documenting/clarifying

modeling difficulties or model changes). Remind me to speak about drawing diagrams

using Word.

5) the most challenging and/or focal segments/features of the model

6) your initial/early modeling attempts, and their consequences and diagnostics

7) your final model (estimation adequacy, fit, estimates, diagnostics, measurement, selected

interpretation of key features, latent effects and explained variance, controlling, overall theory

consequences of the current estimates/model, remaining difficulties/challenges, and future

possibilities).

Models that fit, or that fail-to-fit, can both receive top marks if the modeling is

conducted competently, assessed honestly, and reported clearly/appropriately; so beware making

unreasonable/untenable/indefensible model modification to obtain a fitting model.

In the past, students who rigidly followed the above steps did OK in this class but did

slightly less-well than students who treated the above as guidelines covering the basics while they

attempted to focus on the overall impact or importance of what was learned via their modeling

attempt(s). It is possible to consider the above points as you tell “the story” of whatever you are led

to say about how future research could be improved, or in what direction(s) future research is

prodded, by your modeling attempt. For example, as a minor part of your write-up, or possibly as a

portion of your thinking about your model, you might consider what you would claim if another

researcher had a model/theory that contains the same indicators as your model, and that fits about as