By selecting this option, Prism will perform the unequal variance unpaired t test (sometimes called the unpaired t test with Welch's correction ) O The first choice makes no assumptions about the standard deviations of the populations from which the data in any row or column were sampled from. Selecting this combination of options in the previous two sections results in making one final decision about the standard deviation of each group in the analyses. Each test and the options available in this final section are described below.ġ. There are seven total tests that can be performed for each row, some of which have additional options to consider. Choose test for each rowīased on the options selected in the previous two sections, the final decision to make on the Experimental Design tab of the analysis parameters dialog is which specific test to perform. Moreover, deciding when to use a nonparametric test is not straightforward. This may seem like an advantage (reducing the number of assumptions required about the data), however nonparametric tests have less power. Nonparametric tests are not based on the assumption that the data are sampled from a Gaussian distribution. For example, if you are comparing measurements of blood pressure in two groups, it is OK to match individuals on age or body weight, but it is not OK to match based on their recorded blood pressure. Note that matching should be determined by the experimental design, and should definitely not be based on the variable being analyzed. You measure a variable in individuals with some inherent pairing, such as twins or child/parent pairs.This may be important if uncontrollable experimental conditions vary slightly between preparations You run a laboratory experiment several times, each time with a control and treated preparation handled in parallel.In this situation, one individual may receive one treatment while the other receives an alternative treatment (or serves as a control) Measurements were performed on individuals that were recruited or matched as pairs based on characteristics such as age, ethnic group, or disease severity.Measurements were performed on the same subject at different times (for example, before and after a treatment).Examples of when you may choose this option include: If the option "Paired" is selected, this means that data in the first subcolumn of each main column is paired or matched, the data in the second subcolumn of each main column is paired or matched, and so on. This first question pertains to the relationship of the data within each main group being compared. Based on the answers to the previous two questions, which specific test should Prism perform? Experimental Design: Are the data paired or unpaired? Will the tests assume a Gaussian (Normal) distribution?ģ. The first tab of the Parameters: Multiple t tests (and nonparametric tests) analysis dialog presents a number of options that allow you to specify the type of analysis to perform by answering three questions:Ģ. Prism provides a number of important options for the multiple t test (and nonparametric tests) analysis, allowing you to choose from one of seven different tests to perform for each row of the data table.
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