By Jacqmin-Cadda H.
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It is an estimate of the assumed common variance of the two populations. 2 Let Multivariate test be the mean vector in sample 1 = and similarly for sample 2. We need to test the significance of the difference between and . We will consider first the case where the covariance matrix, which is assumed to be the same in the two samples, is known. Then we will consider the case where an estimate of the covariance matrix needs to be used. 2. using the chi-squared test. is unknown If the covariance matrix is not known, it is estimated using the covariance matrices within each group but pooled.
3 Reliability-Coefficient In cases where composite scales are developed, this measure is useful to assess the reliability of the scales. 9 for market research are typically not sufficient to warrant further analyses using these composite scales. 6 illustrates how to compute means and the correlation matrix for a list of variables in SAS. 7. 9. 9% of the variance. The rotated factor patterm shows that Factor 1 groups variables IT1, IT3, IT4, IT6 and IT7, while Factor 2 reflects variables IT5, IT8 and IT9.
4 Composite Scales A composite scale is built from using multiple items or components measuring the constructs. 1. Note that by convention, circles represent unobserved constructs and squares identify observable variables or measures. 1 31 Reliability of a two-component scale In this section, we show that the reliability of a composite scale has a lower bound. This lower bound is coefficient alpha. The two components of the scale are: The composite scale corresponds to a formative index: Although, a priori, and appear as different true scores, we will see that they must be positively correlated and we will show the impact of that correlation on the reliability of the scale.
Analysis of left-censored longitudinal data with application to viral load in HIV infection by Jacqmin-Cadda H.