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Evaluating the influence of disaggregated survey panel responses on Business Tendency Survey outcomes through RM Anova analysis. Discover the effects of Manufacturing, Retail, and Building sectors on business confidence and activity.
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Evaluating the impact of disaggregated survey panel responses on Business Tendency Survey Results - GM Pellissier - DG Nel * Stellenbosch University, South Africa
Repeated measures analysis of variance (RM_Anova) • The purpose of the RM_Anova procedure is to compare simultaneously the means in several groups/variables and determine if significant changes occurred over a time period
RM_Anova Considerations RM_Anova analyses were considered : • to evaluate the stated hypothesis of no differences in survey results between disaggregated BER panel responses • to determine if significant changes occurred over time between the different groups of disaggregated BER survey results
Implementation of RM_Anova • RM_Anova were implimented to test the hypothesis of similarity, between the survey results generated by the three groups of participating respondents, within each survey quarter as well as between quarterly responses. • There are two main effects 1) survey responses over the total period, called ‘Survey’ and 2) survey responses within each survey quarter, called ‘Quarter’
RM_Anova Assumption • RM_Anova analysis is done under the assumption of compound symmetry i.e. requiring no significant interaction between the stated time series data. If rejected these interactions should be interpreted, otherwise the main effects of ‘Survey’ and ‘Quarter’ can be interpreted
RM_Anova of disaggregated Manufacturing survey results on buss confidence
Conclusion Institutions running Business Tendency surveys based on voluntary panel participation can rest assure that in statistical terms the survey results between Regular and Irregular survey respondents can be interpreted as being the same
Evaluating the impact of disaggregated survey panel responses on Business Tendency Survey Results