Posted by
Alejandro González Heras on
Mar 16, 2021; 3:41pm
URL: http://spssx-discussion.165.s1.nabble.com/Binary-Logistic-Regression-for-Rare-Events-tp5740296p5740304.html
Hi Art,
Indeed, it could be understood as a scale but it does not have a normal distribution:
Dependent variable:
"How much do you believe that fake news influence you?"
1 22 (nothing at all)
2 7
3 19
4 37
5 117
6 260
7 537 (a lot)
Total 999
Now, could this variable explain what it's called "third person effect" (*)?
(IV) "How much do you think that fake news influence public opinion?" (also a likert variable with a non normal distribution)
Multiple linear regression (including other IVs) would be great if a normal distribution could be assumed. That's why we tried to dichotomize the DV into two groups: [1-4] vs [5-7]. Logistic regression would then be nice but we have to face the unequal variable distribution. There is the fact that it is uncommon to think that fake news have little influence in oneself. That's the reason for ordinal regression or the 'count models' which I haven't explored yet. Or the options that tell us about Jon and Bruce, which I understand are linked to R
(*). To put it simply, let me give you the Wikipedia definition: "The third-person effect hypothesis predicts that people tend to perceive that mass media messages have a greater effect on others than on themselves, based on personal biases."
Kind regards,
A
-----Mensaje original-----
De: SPSSX(r) Discussion <
[hidden email]> En nombre de Art Kendall
Enviado el: martes, 16 de marzo de 2021 14:35
Para:
[hidden email]
Asunto: Re: Binary Logistic Regression for Rare Events
Likert item response variables are usually part of a summative scale.
Is your DV a scale or a single variable?
What were the values on the pre-coarsened DV?
Why did you coarsen it to a dichotomy?
-----
Art Kendall
Social Research Consultants
--
Sent from:
http://spssx-discussion.1045642.n5.nabble.com/=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD
=====================
To manage your subscription to SPSSX-L, send a message to
[hidden email] (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD