Exercises

  1. Describe the conceptual meaning of Cronbach’s alpha. If your scale has α = 0.85, how do you interpret that number?
  2. Replicate the estimation of alpha and the item-total correlations for the GDS data presented in text and Figure 11.5 Alpha and item-total correlations for the GDS data. Then replicate the estimation of bootstrapped CI for the subsample of N=50 presented in Alphas and 95% CI for three subsamples and Item-total correlations and 95% CI for three subsamples. Use a seed of 3 and simple random sampling to replicate the selection of the N=50 sample. Then use a seed of 5 and 2000 resamples to estimate bootstrapped CI. By setting the seed values, you should find that your results match those presented in the tables exactly. Refer to Chapter 7 for more information about the bootstrapping process and the general syntax that is required. You can also check your code against that provided on the book website.
  3. Use the engineering data set from the book to do the following:
    1. Make sure that all items are coded in the same direction (recode items where necessary) and calculate alpha for the problem-solving and interest in engineering scales. Also examine the item-total correlations to see whether any items could be removed from the scale to improve reliability.
    2. Bootstrap confidence intervals around the alphas and interpret the replicability of the estimates.
    3. Interpret alpha in terms of quality of measurement, referencing the bootstrapped confidence intervals.
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