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Data Analysis Plan for Analysis of Covariance (MANCOVA) - Statswork

Data Analysis Plan for Analysis of Covariance (MANCOVA)

 

Are you struggling to identify right statistical tool to adjust covariates (CVs) and look at the main effects and interactions on dependent variable? Or in other words Do you wanted to compare several means but controlling for the effect called covariates? Does your data meet basic requirement of one or more dependent categorical variable, one independent variable and one or more continuous covariates? Have you checked covariates are uncorrelated with the independent variables but related to the DV, to avoid diminishing association between DV and IV?, overall, you wanted to look at how some additional variable called a covariate effect the independent variable and remove this effect and see a more accurate picture of the true effect, then applying Analysis of Covariance is the best choice.

At StatsWork, we have successfully completed more 1000 projects using ANOCOVA for dissertations statistics, PhD level statistics, Manuscript Publications, and Text Book publications. Our team of statisticians is completely aware of assumptions of ANOCOVA tool and would able to provide best output required for the data that you had collected for your research.

Our team will check whether the following assumptions are met with your data

  • Missing data
  • Unequal Sample size
  • Outliers _ Both Univariate and Multivariate outliners on the DV and combined DV and CV
  • No Multicollinearity / Singularity – Need to check if covariate is related to another covariate (>0.05), then it will not
  • Normality of Sampling Distribution
  • Homogeneity of Variance and Linearity ; Homogeneity of Regression

We report ANOCOVA Results using standard acceptable format such as APA and other format you request. However, general format of reporting is presented here:

“The ANCOVA for men versus women on pre versus post-test depression scores controlling for SES was found to have no statistically significant main effects, F(1,243) = 1.35, p > .05, interactions, F(1,243) = 2.06, p > .05, or covariates, F(1,243) = 1.03, p > .05…”

We just do not copy past the several outputs but rather we convert all output into proper format. Our Table Format for Reporting ANCOVA Descriptive results from SPSS or SAS is as follows


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Methodology consultationQuestionnaire designData collectionData cleaning Analysis of dataInterpretation of analysisOthers

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