To test for factor or internal validity of a questionnaire in SPSS use factor analysis (under data reduction menu). If the factor structure is similar to what you propose (number of factors, pattern of factor loadings, etc.) then you have evidence of validity (at least of the factorial variety). I prefer factor analyses with PC extraction, the scree plot (or Velicer's MAP test) to determine the number of factors, and Varimax rotation. Others will adamently argue for PAF extraction, but this is really based on PC extraction in the first place.. Some will argue for obligue rotation, but then cannot specify how to set the delta parameter (other than use the default = 0).
IMHO!
Psychology Professor and statistics instructor for 25 years.
They (V1, V2 , ...) are the second participants' answers to questions that are collected a few time after initial answers (Q1, Q2 , ...). Then, the correlation of Q and V interprete as the validity of questionnaire.
But I know this is reliability test of questionnaire at same time on two groups or different times on same groups. Could you kindly inform me difference between reliability and validity test?
Reliability is the internal consistency of the data between the variances of the observed value and true value with or without the error values. It depends on the error value extraction. The Validity per say is feasible with the Factor analysis or confirmatory factor analysis. It is about the possibility of all the items proposed in the questionnaire remain as factor or some of the items get excluded after the factor analysis.
there are several tests and methods for evaluation of validity depending on what type of validity you are looking for. For example, if you need content validity! construct validity! outcome validity! each of them need an especial examination. Confirmatory factor analysis-special form of factor analysis- is used to test construct validity. If you wish use SPSS for this case you need instull SPSS Amos on your spss. hopefully this explanation and my article attached here can help you.
Reliability of the questionnaire can be assured by using Cronbach’s formula of finding alpha values(internal consistency method) and inter-item correlation (relationship among items). Validity can be assured(convergent and concurrent) by obtaining the correlation value using Spearman’s formula
Cronbach's alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. It is considered to be a measure of scale reliability. A "high" value for alpha does not imply that the measure is unidimensional. If, in addition to measuring internal consistency, you wish to provide evidence that the scale in question is unidimensional, additional analyses can be performed. Exploratory factor analysis is one method of checking dimensionality. Technically speaking, Cronbach's alpha is not a statistical test - it is a coefficient of reliability (or consistency). Cronbach's alpha can be written as a function of the number of test items and the average inter-correlation among the items. Below, for conceptual purposes, we show the formula for the standardized Cronbach's alpha: You can read more by details in this link