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Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: Analyzing ordinal data with metric models: What could possibly go wrong?

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?

Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: Analyzing ordinal data with metric models: What could possibly go wrong?

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?

Many thanks :)

Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: https://scholarworks.iu.edu/dspace/bitstream/handle/2022/21970/2018-03-23_wim_kruschke_ordinal-metric_flyer.pdf?sequence=1

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?

Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: Analyzing ordinal data with metric models: What could possibly go wrong?

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?

Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: https://scholarworks.iu.edu/dspace/bitstream/handle/2022/21970/2018-03-23_wim_kruschke_ordinal-metric_flyer.pdf?sequence=1

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?

Many thanks :)

Psychologists often use the general linear model with ordinal independent/dependent variables (i.e. Likert scales to measure 'levels' of a psychological trait. For example, assigning numbers to the labels: "Strongly Disagree, Disagree, Neither, Agree, Strongly Agree")

Apparently, Dr. John K. Kruschke gave a talk explaining how this leads to errors and recommended ordered probit models instead: https://scholarworks.iu.edu/dspace/bitstream/handle/2022/21970/2018-03-23_wim_kruschke_ordinal-metric_flyer.pdf?sequence=1

Unfortunately, I could not attend.

Could someone please explain when and why psychologists should use ordered probit models rather than the general linear model?