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Category Archives: Clinical Trials

Factorial Designs


In this section we will describe the completely randomized factorial design. This design is commonly used when there are two or more factors of interest. Recall, in particular, the difference between an observational study and a designed experiment. Observational studies involve simply observing characteristics and taking measurements, as in a sample survey. A designed experiment […]

The Logic Behind Meta-analysis – Random-effects Model


The fixed model starts with the assumption that true effect size is the same in all studies. However, in many systematic reviews this assumption is implausible. When we decide to incorporate a group of studies in a meta-analysis, we assume that the studies have enough in common that it makes sense to synthesize the information, […]

The Logic Behind Meta-analysis – Fixed-ffect Model


Effect Size (Based on Means) When the studies report means and standard deviations (more precisely, the sample standard error of the mean), the preferred effect size is usually the raw mean difference, the standardized mean difference mean difference, or the response ratio. When the outcome is reported on a meaningful scale and all studies in […]

Linear Regression


The Regression Equation When analyzing data, it is essential to first construct a graph of the data. A scatterplot is a graph of data from two quantitative variables of a population. In a scatterplot, we use horizontal axis for the observations of one variable and a vertical axis for the observations of the other variable. […]

Inferences for Population Standard Deviations


Inferences for One Population Standard Deviation Suppose that we want to obtain information about a population standard deviation. If the population is small, we can often determine 𝜎 exactly by first taking a census and then computing 𝜎 from the population data. However, if the population is large, which is usually the case, a census is […]