Dear all, thanks in advance.
I've got a question.
I'm validating a questionnaire where I have three factors.
For each of these factors I want to investigate internal homogeneity.
At this purpose I'm using the command "loevh".
I read that H values higher than 0.4 are considered acceptable.
Anyway I don't understand the test of Guttamn's errors (exepected vs observed). What does it tell us?
How to interpretate the p value?
Does anyone know it?
I thank you all.
Gianfranco
. loevh q1 q2 q10 q13 q18
Observed Expected Number
Mean Guttman Guttman Loevinger H0: Hj<=0 of NS
Item Obs Score errors errors H coeff z-stat. p-value Hjk
---------------------------------------------------------------------------------------------------
q1 116 3.7672 229 444.75 0.48510 9.5657 0.00000 0
q2 116 3.4052 305 513.23 0.40573 8.0033 0.00000 0
q10 116 3.9828 281 441.07 0.36291 7.3216 0.00000 0
q13 116 3.9914 251 435.03 0.42302 8.5137 0.00000 0
q18 116 3.8707 268 473.20 0.43364 8.7006 0.00000 0
---------------------------------------------------------------------------------------------------
Scale 116 667 1153.64 0.42183 13.2764 0.00000
I've got a question.
I'm validating a questionnaire where I have three factors.
For each of these factors I want to investigate internal homogeneity.
At this purpose I'm using the command "loevh".
I read that H values higher than 0.4 are considered acceptable.
Anyway I don't understand the test of Guttamn's errors (exepected vs observed). What does it tell us?
How to interpretate the p value?
Does anyone know it?
I thank you all.
Gianfranco
. loevh q1 q2 q10 q13 q18
Observed Expected Number
Mean Guttman Guttman Loevinger H0: Hj<=0 of NS
Item Obs Score errors errors H coeff z-stat. p-value Hjk
---------------------------------------------------------------------------------------------------
q1 116 3.7672 229 444.75 0.48510 9.5657 0.00000 0
q2 116 3.4052 305 513.23 0.40573 8.0033 0.00000 0
q10 116 3.9828 281 441.07 0.36291 7.3216 0.00000 0
q13 116 3.9914 251 435.03 0.42302 8.5137 0.00000 0
q18 116 3.8707 268 473.20 0.43364 8.7006 0.00000 0
---------------------------------------------------------------------------------------------------
Scale 116 667 1153.64 0.42183 13.2764 0.00000