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1) In MANCOVA, Independent variables, Dependent variables and covariate must each confirm to a specific level...

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Statistics

1) In MANCOVA, Independent variables, Dependent variables andcovariate must each confirm to a specific level of measurement.List the correct level of measurement for each of the variablelisted Independent variables, Dependent variables and covariate

2) Differentiate between a Total Effect, Direct Effect andIndirect Effect within the decomposition of effects approach fordetermining statistical mediation

3) Describe the similarities and differences between simplemediation and moderation atleast four points

4) When and why would one choose to interpret pillai's Tracemultivariate test statistics over wilks Lambda?

5) What is bootstrapping and why is it used in statisticalanalyses involving mediation?

6) How does MANOVA differe from ANOVA. When would you select torun a MANOVA over an ANOVA and why would MANOVA be advantageous insuch situations.

7) Define a coavriate. How do you choose a covariate?

Answer & Explanation Solved by verified expert
4.0 Ratings (600 Votes)
aMultivariate analysis of covariance MANCOVA is a statisticaltechnique that is the extension of analysis of covariance ANCOVABasically it is the multivariate analysis of variance MANOVAwith a covariates In MANCOVA we assess for statisticaldifferences on multiple continuous dependent variables by anindependent grouping variable while controlling for a thirdvariable called the covariate multiple covariates can be useddepending on the sample sizeLevel and Measurement of the VariablesIn MANCOVA assumes that the independent variables arecategorical and the dependent variablesare continuous or scale variablesCovariates can be either continuous ordinal ordichotomousc Similarities and differences between simple mediationand moderationBoth mediation and moderation have to do with checking on how athird variable fits into that relationship For the purposes ofunderstanding these two concepts this is where the similaritiesendModeration is a way to check whether that third variableinfluences the strength or direction of the relationship between anindependent and dependent variable An easy way to remember this isthat the moderator variable might change the strength of arelationship from strong to moderate to nothing at allIt is almost like a turn dial on the relationship as you changevalues of the moderator a statistical relationship that youobserved before might dissolve away For example if you expectedthat the length of time studying related to the grades on acalculus test you would probably be right Lets say there is astrong relationship between time spent studying and gradesHowever that relationship may not hold true across the boardsomething like grade level might be a possible moderator If youswitch the value of this moderator from college student toelementary    See Answer
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