3.6 Hypothesis testing Although in experimental research ANOVA analysis is commonly preferred, logistic analysis and multiple regression analysis will be used in this research. Logistic analysis will be conducted to test H1. Multiple regression analysis will be conducted in order to find out if the independent variables have any effect on the dependent variables for H2, H3 and H7. For the independent variable, degree of personalization, which was manipulated during our quasi-experiment, we create four dummies to test the difference among these treatments: Ad1: dummy variable for contextual targeting: 1 contextual, 0 control – – Ad2: dummy variable for connection targeting: 1 connection, 0 control – – Ad3: dummy variable for search engine targeting: 1 search engine, 0 control – – Ad4: dummy variable for profile-based targeting: 1 profile, 0 control – – Furthermore, the independent variable, degree of personalization was coded by the result of the pretest, thus control group = 0, contextual group = 1, connection group = 2, search engine group = 3, profile-based group = 4. Analysis1: Testing H1 A logistic regression was conducted to test this hypothesis, because the dependent variable, brand recall, is a categorical variable divided into two groups (0-no, 1-yes), meanwhile, the independent variable (DP) is also a categorical variable. Brand recall was collected by asking our subjects whether they remember the brand of the ad they just saw on the For the subjects who answered yes but cannot tell “Facebook page”. anything related with the brand, we also value them with The goal of logistic “0”. regression is to predict an which may or may not occur, so a logistic ‘event’ regression was suitable to be conducted. Brand recall term (1) =β0 + β1DP+error The significance and sign of the coefficient of will be checked for H1. β1 Analysis2: Testing H2 and H6
3.6 Hypothesis testing Although in experimental research ANOVA analysis is commonly preferred, logistic analysis and multiple regression analysis will be used in this research. Logistic analysis will be conducted to test H1. Multiple regression analysis will be conducted in order to find out if the independent variables have any effect on the dependent variables for H2, H3 and H7. For the independent variable, degree of personalization, which was manipulated during our quasi-experiment, we create four dummies to test the difference among these treatments: Ad1: dummy variable for contextual targeting: 1 – contextual, 0 – control Ad2: dummy variable for connection targeting: 1 – connection, 0 – control Ad3: dummy variable for search engine targeting: 1 – search engine, 0 – control Ad4: dummy variable for profile-based targeting: 1 – profile, 0 – control Furthermore, the independent variable, degree of personalization was coded by the result of the pretest, thus control group = 0, contextual group = 1, connection group = 2, search engine group = 3, profile-based group = 4. Analysis1: Testing H1 A logistic regression was conducted to test this hypothesis, because the dependent variable, brand recall, is a categorical variable divided into two groups (0-no, 1-yes), meanwhile, the independent variable (DP) is also a categorical variable. Brand recall was collected by asking our subjects whether they remember the brand of the ad they just saw on the “Facebook page”. For the subjects who answered yes but cannot tell anything related with the brand, we also value them with “0”. The goal of logistic regression is to predict an ‘event’ which may or may not occur, so a logistic regression was suitable to be conducted. Brand recall =β0 + β1DP+error term (1) The significance and sign of the coefficient of β1 will be checked for H1. Analysis2: Testing H2 and H6
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