Strategy for statistically testing a new diabetics drug
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Let's say I have a new drug that I think helps diabetics. So I perform clinical trials in accordance with the FDA requirements. I give one randomly selected groups of diabetics the drug, and another sample gets a placebo pill. The diabetics who get the pill improve, the controls do not. I perform a t test on the data. What is the independent variable? The dependent variable? The null hypothesis?
The above is a cross sectional research design. Here is another strategy. I have only one group of diabetics. I evaluate them and give them the pill. I bring them in next week and evaluate them again, give them another pill. The following week I do the same, and on and on for several months. This is a longitudinal design, or a "repeated measures" design. I would have to analyze this with a "dependent" t test, or since the groups are measured over and over again, a repeated measures ANOVA. In these designs, the subjects are used as their own controls.
Which strategy or research design do you think is best?
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The strategy for statistically testing a new diabetics drugs are examined.
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I would say both approaches have their pros and cons. Before we get to that, your independent variable (for both designs) is what you're manipulating: the drug (whether people have the drug or the placebo). The dependent variable (for both designs) is what you're measuring: whatever 'helps diabetics' means - maybe more consistent blood sugar levels or something like that. Your null hypothesis is always that your ...
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