BackgroundStructural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators.DiscussionMultiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms.SummaryWe recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

With the ideational turn in populism studies (Mudde and Rovira Kaltwasser 2013), researchers have started to conceptualize and measure populism as a set of attitudes individuals hold about politics and society (e.g. Akkerman et al. 2014; Elchardus and Spruyt 2014;Hawkins et al. 2012;Rooduijn 2014b;Spruyt 2014;Stanley 2011). As proposed in the introduction to this volume, such attitudes are ordinarily dormant, but may be activated given a favorable context for populist discourse and its articulation by political actors. The measurement of these attitudes, however, has been far from uniform, as the review by Van Hauwaert, Schimpf, and Azevedo in 1 Contact author: BCS. BCS wrote the paper with substantial support from BS; BCS, IA, LL ran the analyses; BCS and LL designed the study; IA, EA, NB, YMC, GD, GR, SR, MS collected data, provided valuable comments and edits, and are listed in alphabetical order; LL led the project. The authors would like to thank Andreea Nicutar, Daniel Kovarec, Elisa Totino, Federico Vegetti, Selina Kurer, and Sharon Belli for their help with questionnaire translation and survey implementation, and Sebastian Jungkunz and Nemanja Stankov for assistance with data cleaning and writing the codebooks.the previous chapter shows. The basis of the most commonly scale used today was set in Hawkins, Riding, and Mudde (2012). It was extended into the popularized six-item version by Akkerman, Mudde, and Zaslove (2014), and used by Spruyt et al. 2016, and in the chapters by Andreadis and Ruth; Singer et al.; and Busby et al. in this volume.However, as Van Hauwaert, Schimpf, and Azevedo have shown in their chapter, there is room for improvement in scale development. From a survey methodology perspective, the items fail to identify strong levels of populism and anti-populism and can only discriminate among moderate forms of it. They are not polarizing enough, as there seems to be a general trend of agreement: for all countries and items, the item averages are above the scales' middle point. A further limitation of the existing measures is that in most scales all items are positively wordedmeaning that more agreement indicates more populism. For this reason it is impossible to discriminate between actual agreement with the content and acquiescence bias.Our purpose with this study is to tackle the issue of scale development following practices common in psychology but that have yet to make their way into political science. We start with a large number of items, and use various techniques to select the few ones that work better at capturing populist attitudes. Next we test which items are invariant across countriesi.e., whether they measure the same thing, the same way, in different countries. Recent research has shown that several scales, some of which have been around for decades in social sciences, should not be used for cross-country comparisons because the measure is not invariant across cultures (Alemán and Woods 2016, Ariely and Davidov 2010, Piurko et al. 2011. Our analyses result in a short questio...

We explore the relationship between populist attitudes and conspiratorial beliefs on the individual level with two studies using American samples. First, we test whether and what kinds of conspiratorial beliefs predict populist attitudes. Our results show that belief in conspiracies with greedy, but not necessarily purely evil, elites are associated with populism. Second, we test whether having a conspiratorial mentality is associated with all separate sub-dimensions of populist attitudespeople-centrism, anti-elitism, and a good-versus-evil view of politics. Results show a relation only with the first two, confirming the common tendency of both discourses to see the masses as victims on elites' hands. These findings contribute to research on the correlates of populism at the individual level, which is essential to understanding why this phenomenon is so strong in contemporary democracies.

With the recent upsurge of populism in developed and transition democracies, researchers have started measuring it as an attitude. Several scales have been proposed for this purpose. However, there is little direct comparison between the available alternatives. Scholars who wish to measure populist attitudes have little information available to help select the best scale for their purposes. In this article, we directly compare seven populist attitudes scales from multiple perspectives: conceptual development, questionnaire design, dimensionality, information, cross-national validity, and external validity. We use original survey data collected online from nine countries in Europe and the Americas, with around 250 participants per country, in which all seven batteries of questions were present. Results show that most scales have important methodological and validity limitations in at least one of the dimensions tested, and should not be used for cross-national comparative research. We recommend populist attitudes items that work better at capturing populism, and more generally provide guidelines for researchers who want to compare different scales that supposedly measure the same construct.

Almost forty years ago, evidence from large studies of adult twins and their relatives suggested that between 30-60% of the variance in social and political attitudes could be explained by genetic influences. However, these findings have not been widely accepted or incorporated into the dominant paradigms that explain the etiology of political ideology. This has been attributed in part to measurement and sample limitations, as well the relative absence of molecular genetic studies. Here we present results from original analyses of a combined sample of over 12,000 twins pairs, ascertained from nine different studies conducted in five democracies, sampled over the course of four decades. We provide evidence that genetic factors play a role in the formation of political ideology, regardless of how ideology is measured, the era, or the population sampled. The only exception is a question that explicitly uses the phrase “Left-Right”. We then present results from one of the first genome-wide association studies on political ideology using data from three samples: a 1990 Australian sample involving 6,894 individuals from 3,516 families; a 2008 Australian sample of 1,160 related individuals from 635 families and a 2010 Swedish sample involving 3,334 individuals from 2,607 families. No polymorphisms reached genome-wide significance in the meta-analysis. The combined evidence suggests that political ideology constitutes a fundamental aspect of one’s genetically informed psychological disposition, but as Fisher proposed long ago, genetic influences on complex traits will be composed of thousands of markers of very small effects and it will require extremely large samples to have enough power in order to identify specific polymorphisms related to complex social traits.