Assessing reliability of a questionnaire: What best measure dimensionality, problematic items, and whether to use alpha, lambda6 or some other index?

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edited Jun 6, 2011 at 13:37

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I am analyzing scores given by participants attending an experiment. Firstly, I would likewant to estimate estimate the reliability of my questionnaire which is composed of 6 items aimed at estimating the attitude of the participants towards a product.

I computed Cronbach's alpha when considering ontreating all items as a single scale (alpha was about 0.6) and deleting one item at a time (max alpha was about 0.72). I know that alpha can be underestimated and overestimated depending on the number of items and the dimensionality of the underlying construct. So I also performed a PCA. This analysis revealsrevealed that there arewere three principal components explaining about 80% of the variance. So, my questions are all about: How how can I proceed now?

Do I need to perform alpha computation on each of these dimension?
Do I have remove the items affecting reliability?

Further, searching on the web I found there is another measure of reliability: the lambda6 of guttman.

What are the main differences between this measure and alpha?
What is a good value of lambda?

I am analyzing scores given by participants attending an experiment. Firstly, I would like to estimate the reliability of my questionnaire which is composed of 6 items aimed at estimating the attitude of the participants towards a product.

I computed Cronbach's alpha when considering on all items (alpha about 0.6) and deleting one item at a time (max alpha about 0.72). I know that alpha can be underestimated and overestimated depending on the number of items and the dimensionality of the underlying construct. So I also performed a PCA. This analysis reveals that there are three principal components explaining about 80% of the variance. So, my questions are all about: How can I proceed now?

Do I need to perform alpha computation on each of these dimension?
Do I have remove the items affecting reliability?

Further, searching on the web I found there is another measure of reliability: the lambda6 of guttman.

What are the main differences between this measure and alpha?
What is a good value of lambda?

I am analyzing scores given by participants attending an experiment. I want to estimate the reliability of my questionnaire which is composed of 6 items aimed at estimating the attitude of the participants towards a product.

I computed Cronbach's alpha treating all items as a single scale (alpha was about 0.6) and deleting one item at a time (max alpha was about 0.72). I know that alpha can be underestimated and overestimated depending on the number of items and the dimensionality of the underlying construct. So I also performed a PCA. This analysis revealed that there were three principal components explaining about 80% of the variance. So, my questions are all about how can I proceed now?