SEM Musical TEN!
Lyrics by Alan Reifman (retread from previous years)
(May be sung to the tune of “Let’s Get it Started,” Will Adams et al. for the Black Eyed Peas)
(Softly) The models keep runnin-runnin, and runnin-runnin, and runnin-runnin, and runnin-runnin, and runnin-runnin, and runnin-runnin, and runnin-runnin, and runnin-runnin, and...
We’re back again, to have some fun,
We’re gonna bust some rhyme, have a good time,
We’re gonna sing some songs, about SEM technique,
Access your inner geek, let your voices speak,
SEM is different, your measurement model’s explicit,
The whole model, gets tested for fit,
Is it identified? We know how hard you’ve tried,
Knowns and unknowns, side by side,
It takes you on a ride, finally you’re satisfied,
Your output’s now just fine, you’ve arrived, you can take pride…
NFI, TLI, CFI,
Calculate estimates, let it run, have some fun, yeah…
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
Yeah...
Build your constructs, get this straight,
Make sure the indicators, correlate,
Draw your pathways, residuals too,
Don’t leave out, the fixed 1 value,
Take your time, think it through,
Don’t worry if you’re new, we’ll walk with you,
Step by step, right up the pyramid,
For SEM, we’re really groovin,’
Hope you get an acceptable solution,
Submit your model and get it movin,’
NFI, TLI, CFI,
Calculate estimates, let it run, have some fun, yeah…
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
SEM Musical (TEN!), SEM Musical (HERE!),
Yeah...
The Part That’s Error-Free
Lyrics by Alan Reifman
(May be sung to the tune of “Biggest Part of Me,” David Pack for Ambrosia)
Boxes, they hold the manifestations,
Bubbles, are error locations,
Constructs, house the shared variation,
They're the part, that’s error-free,
Loadings, show measures, are correlated,
That makes, indicators validated,
Errors, in the bubbles, they are gated,
So constructs, are error-free,
Well...
You remove error,
And the paths, become more true*,
This is such, a key thing,
Latent constructs, do for you,
So draw it now,
Tell measurement error, to shoo.
You can estimate, the paths,
Without error, troubling you,
Sometimes, you have just, total-scale measures,
Of those, certain constructs, that you treasure,
Alpha, gives a way to block displeasure,
Controls, unreliability,
Parcels, a technique, that can’t be plainer,
Items, placed into, random containers,
These sets, can then serve, as indicators,
Constructs now, are error-free,
Well-l-l-l-l...
You remove error,
And the paths, become more true,
This is such, a key thing,
Latent constructs, do for you,
So draw it now,
Tell the measurement error, to shoo,
You can estimate, the paths,
Without error, troubling you,
(Instrumentals)
It’s an SEM hallmark,
Going back to CFA,
It’s a major advantage, of using LV’s,
Not all techniques, give you this,
Measurement error, doesn’t go away,
So use latent constructs, to be error-free,
Be error-free,
Be error-free...
*Stephenson, M. T., & Holbert, R. L. (2003). A Monte Carlo simulation of observable versus latent variable structural equation modeling techniques. Communication Research, 30, 332-354.
See also previous lecture modules here and here.
Those Kinds of Paths (Are Autoregressive)
Lyrics by Alan Reifman
(May be sung to the tune of “Because the Night,” Springsteen/Smith)
Panel models, longitudinally,
Follow the same people, over time,
Each major construct, we include repeatedly,
It gets us the time-ordering, of causality,
So, come on now, no hand-calculated math,
In cross-lagged models, we run paths,
From Construct A at one time, to B at the next,
We also have paths, from the same construct,
Time 1 to Time 2, and Time 2 to Time 3,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Autoregressive paths, play a crucial role,
They control for earlier levels, of a later DV,
So when a cross-lagged path, is significant,
It shows association, beyond stability,
So, come on now, no hand-calculated math,
In cross-lagged models, we run paths,
From Construct A at one time, to B at the next,
We also have paths, from the same construct,
Time 1 to Time 2, and Time 2 to Time 3,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
(Guitar solo)
These kinds, of paths,
Predict, to later versions, of themselves,
Without them, analyses would lack rigor,
So include them...
Time 1 to Time 2, Time 2 to Time 3,
Time 1 to Time 2, Time 2 to Time 3,
Time 1 to Time 2, Time 2 to Time 3,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability,
Those kinds of paths, are auto-regressive,
Those kinds of paths, test stability...
Constructs (Don’t be Afraid of Changing!)
Lyrics by Diane Wittie
(May be sung to the tune of “Landslide,” Stevie Nicks)
Gathered the data, and they abound,
I cleaned them up, then I went to town,
And I saw some variables, that looked interesting,
And now my sleep, would be sound,
Oh, yes I can begin, naming latent constructs,
But will those, constructs make any sense?
Will they adequately represent,
What I envision?
Can I implement, my central concepts?
Uh-hum, I do think so,
Well, don’t be, afraid of changing,
’Cause your constructs, need to make sense,
Think through, your decisions,
You may need, revisions,
Don't do anything, you'll rue,
(Brief guitar)
So, don’t be, afraid of changing,
’Cause your constructs, need to make sense,
Think through, your decisions,
You may need, revisions,
Don't do anything, you'll rue,
To your theory, be true,
So, analyze your data, see what you've found,
Your model, may earn great renown!
If you see factor loadings, at plus or minus .4,
Well maybe, high points you will score,
If you see structural paths, that are significant,
Yes, high points, you will score!
