discussant


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To analyze the selection mechanism, we employ logistic regression models and base the analysis on assessing whether the dyadic relationship between a respondent and his or her discussant persists along the two waves.
Perceived agreement between the respondent and his or her discussant is thus the main predictor, and it is constructed by comparing vote choices of respondents and their discussants in the pre-electoral wave.
w1] is disagreement with discussant in the pre-electoral wave (based on reported respondent and discussant vote choices); [SOC_CIR.
The strength of party identification does not influence the likelihood of maintaining a discussant in the subsequent wave.
In Model 1, it is possible to see that disagreement in Wave 1 does not lead to a significant change in naming the same discussant in Wave 2.
Model 2, by means of a two-way interaction between the discussant's social circle and disagreement, shows what happens to selection strategies when we consider both these characteristics of the main discussant.
This residual network is defined as all the respondent's discussants, except for the discussant involved in the particular dyad being analyzed.
We anticipated this problem by altering the order in which we asked questions about discussant vote preferences.
A faster mean response time in the residual network is associated with a more rapid response time for each of the individual judgments about discussant preferences, and therefore it needs to be controlled.
In the second set of factors are variables that concern the relationship between the main respondent and the discussant.
Similarly, the accessibility of the judgment does not depend on the respondent's perception regarding Proportion of the Residual Network that Agrees with the Discussant.
How do the accessibility and extremity of partisan preferences, both for main respondents and discussants, affect the accessibility of respondent perceptions about discussant preferences?