People Prefer Politicians with Matching Implicit Motives: A Study on the Achievement and Affiliation Motives

2021 ◽  
Author(s):  
Madelijn Strick ◽  
Erik Bijleveld

ObjectiveFor centuries, researchers have been interested in the factors determining political preference. These four studies tested the prediction that a match between political leaders’ and voters’ implicit motives – i.e., non-conscious tendencies to strive for particular social rewards – predicts the appeal of leaders.MethodWe used student samples in all studies (Study 1a: N = 100; Study 1b: N = 52; Study 2: N = 72; Study 3: N = 62). We assessed two implicit motives: (a) the achievement motive, which refers to striving for excellence, and (b) the affiliation motive, which refers to striving for social harmony. Correlational analyses and polynomial regression with response surface analysis were used to assess the relation between implicit motives and political preference.ResultsParticipants were more likely to positively evaluate and vote for politicians whose speeches indicated a motive profile that matched their own implicit motives. Thus, people who are relatively achievement-motivated prefer relatively achievement-motivated candidates, and participants who are relatively affiliation-motivated prefer relatively affiliation -motivated candidates. Conversely, explicitly measured motives did not have these predictive effects.ConclusionsThese results indicate that individual differences in implicit motives play a significant role in political preference.

2010 ◽  
Vol 25 (4) ◽  
pp. 543-554 ◽  
Author(s):  
Linda Rhoades Shanock ◽  
Benjamin E. Baran ◽  
William A. Gentry ◽  
Stacy Clever Pattison ◽  
Eric D. Heggestad

2012 ◽  
Vol 535-537 ◽  
pp. 1564-1568
Author(s):  
Huang Huang ◽  
Yong Ling Yu ◽  
Wei Kong

In this study, the response surface methodology was used to optimize parameters of the diluted hydrochloric acid hydrolysis method, which was adopted to separate the polyester-cotton blend fiber. The four parameters reaction time, mass fraction of hydrochloric acid, reaction temperature and solid-liquid ratio were determined by the single factor experiment as they are significant for the process of separation. By introducing the experiment of four factors on three levels designed by Box-Benhnken central composite method, a quadric polynomial regression model for the fiber weight loss rate was established. And the response surface graphs were plotted to illustrate the optimizing process. The response surface analysis determined that the optimized value of the four parameters were 98 minutes, 10.7%, 96.5 °C and 4.3 g/100ml respectively. Under these conditions, polyester-cotton blend fiber was completely separated.


2018 ◽  
Author(s):  
Felix D. Schönbrodt ◽  
Sarah Humberg ◽  
Steffen Nestler

Dyadic similarity effect hypotheses state that the (dis)similarity between dyad members (e.g., the similarity on a personality dimension) is related to a dyadic outcome variable (e.g., the re- lationship satisfaction of both partners). Typically, these hypotheses have been investigated by using difference scores or other profile similarity indices as predictors of the outcome variables. These approaches, however, have been vigorously criticized for their conceptual and statistical shortcomings. Here, we introduce a statistical method that is based on polynomial regression and addresses most of these shortcomings: Dyadic response surface analysis (DRSA). This model is tailored for similarity effect hypotheses and fully accounts for the dyadic nature of relationship data. Furthermore, we provide a tutorial with an illustrative example and reproducible R and Mplus scripts that should assist substantive researchers in precisely formulating, testing, and interpreting their dyadic similarity effect hypotheses.


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