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Generic Inderal -LA (Propranolol, Inderal -LA® equivalent)
Propranolol is in a group of medications called beta-blockers. Beta-blockers affect the heart and circulation of blood flow. Propranolol is used to treat tremors, angina (chest pain), hypertension (high blood pressure), heart rhythm disorders, and other heart or circulatory conditions. It is also used to treat or prevent heart attack, and to reduce the severity and frequency of migraine headaches. Propranolol may also be used for purposes other than those listed in this medication guide.
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40mg
| Quantity | Price | Price per pill | Returning customer price | Bonus | |
|---|---|---|---|---|---|
| 30 | € 40.81 | € 1.36 | € 36.19 | ---- | Add to cart |
Drug Medical Information
AGE AND BEHAVIOR: RESEARCH METHODS - COHORT AND TIME OF MEASUREMENT CONFOUNDED - CROSS-SEQUENTIAL STRATEGY - EXPERIMENTAL DESIGN
The cross-sequential design can best be described as a combination of cross-sectional and longitudinal studies. Here is a shortened and approximate version of how Schaie and Labouvie-Vief (1974) carried it out in their study on intelligence .
In 1956 people of seven age-cohort groups were tested. This is represented at the top of Table 19.4 by "Cohort" and "Mean Age" under the heading "1956, Test 1." Then, seven years later, they retested these people, and this is represented as "1963, Test 2." The upper part of Table 19.4 shows that Test 1 scores are listed by capital letters (A, B, C . . .) with the average of them being I. Test 2 scores are listed by lower case letters (a, b, c . . .) and their average is II. (There was still a third testing in 1970, but for purposes of an easier understanding of the cross-sequential design, only the first two test periods will be considered, although the principles of analysis are the same with two as with more than two testings.)
It will be recalled that the cross-sectional studies confound age and cohort, and the longitudinal studies confound age and time of testing. The cross-sectional study and a longitudinal study with these confounds. Cross-sectional, there are seven age-cohort groups, and longitudinally, there are two age-time of testing groups (1956 versus 1963). The statistical technique called analysis of variance is now applied: In essence, this technique asks three questions of the data. The first is, are the seven age-cohort groups different in regard to their test scores? This is answered by comparing scores A + a with B + b, C + c . . . and G + g. The second question is, are the scores of Test Time 2 different from those of Test Time 1? This is answered by comparing I and II, the averages of the two times of testing. The third question is the most interesting and, typically, the most important. Do scores change from Time 1 to Time 2 in a greater way for one age-cohort group than for another? This is answered by comparing A — a with B — b,C — C, G — g.
Note that while the above was described in terms of the same people taking the tests at Time 1 and Time 2 (called repeated measures), the design applies also to different, but comparable, people taking the test at Time 1 and Time 2 (independent measures). In fact, Schaie, Labouvie, and Buech (1973) used this latter design.
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