Analysis of variance--why it is more important than ever

Analysis of variance (ANOVA) is an extremely important method in exploratory and confirmatory data analysis. Unfortunately, in complex problems (e.g., split-plot designs), it is not always easy to set up an appropriate ANOVA. We propose a hierarchical analysis that automatically gives the correct ANOVA comparisons even in complex scenarios. The inferences for all means and variances are performed under a model with a separate batch of effects for each row of the ANOVA table. We connect to classical ANOVA by working with finite-sample variance components: fixed and random effects models are characterized by inferences about existing levels of a factor and new levels, respectively. We also introduce a new graphical display showing inferences about the standard deviations of each batch of effects. We illustrate with two examples from our applied data analysis, first illustrating the usefulness of our hierarchical computations and displays, and second showing how the ideas of ANOVA are helpful in understanding a previously fit hierarchical model.Comment: This paper discussed in: [math.ST/0508526], [math.ST/0508527], [math.ST/0508528], [math.ST/0508529]. Rejoinder in [math.ST/0508530

Emulating interviewers in an online survey: Experimental manipulation of 'do-not-know' over the phone and on the web.

[Dataset available: http://hdl.handle.net/10411/17676]

Mode effect or question wording? Measurement error in mixed mode surveys.

[Dataset available: http://hdl.handle.net/10411/17672]

Interviewer Effects on Nonresponse

In face-to-face surveys interviewers play a crucial role in making contact with and gaining cooperation from sample units. While some analyses investigate the influence of interviewers on nonresponse, they are typically restricted to single-country studies. However, interviewer training, contacting and cooperation strategies as well as survey climates may differ across countries. Combining call-record data from the European Social Survey (ESS) with data from a detailed interviewer questionnaire on attitudes and doorstep behavior we find systematic country differences in nonresponse processes, which can in part be explained by differences in interviewer characteristics, such as contacting strategies and avowed doorstep behavior.

Does ethnic diversity erode trust? Putnams hunkering down thesis reconsidered

We use a multi-level modelling approach to estimate the effect of ethnic diversity on measures of generalized and strategic trust using data from a new survey in Britain with a sample size approaching 25,000 individuals. In addition to the ethnic diversity of neighbourhoods, we incorporate a range of indicators of the socio-economic characteristics of individuals and the areas in which they live. Our results show no effect of ethnic diversity on generalized trust. There is a statistically significant association between diversity and a measure of strategic trust, but in substantive terms, the effect is trivial and dwarfed by the effects of economic deprivation and the social connectedness of individuals

Protect Your Sleep When Work is Calling:How Work-Related Smartphone Use During Non-Work Time and Sleep Quality Impact Next-Day Self-Control Processes at Work

In view of the rapid development of information and communication technologies, the present study sheds light on how work-related smartphone use during non-work time affects employees' subsequent working day. Specifically, we examine work-related smartphone use and sleep quality as moderators of next-day self-control processes at work. Theorizing that work-related smartphone use and self-control demands deplete a common limited regulatory resource, we suggest a strengthening two-way interaction between work-related smartphone use during non-work time and next-day self-control demands at work in predicting employees' ego depletion at work. Moreover, in a three-way interaction, we analyze whether this interaction depends on employees' sleep quality, assuming that when intensive work-related smartphone use is followed by high-quality sleep, the taxed regulatory resource can replenish overnight. Results from our diary study covering 10 working days (n = 63) indicate that after evenings with high work-related smartphone use, employees experience disproportionate levels of ego depletion when dealing with self-control demands at work. Sleep quality, however, attenuates this interaction. In cases of high sleep quality, next-day self-control processes at work are no longer affected by work-related smartphone use. Based on these findings, we discuss implications for employees and employers regarding work-related smartphone use and the relevance of sleep in replenishing drained resources

Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage across Countries and over Time

With the decrease of landline phones in the last decade, telephone survey methodologists face a new challenge to overcome coverage bias. In this study we investigate coverage error for telephone surveys in Europe over time and compare two situations: classical surveys that rely on landline only with surveys that also include mobile phones. We analyzed Eurobarometer data, which are collected by means of face-to-face interviews and contain information on ownership of landline and mobile phones. We show that for the period 2000-2009, time has a significant effect on both mobile phone penetration and coverage bias. In addition, the countries’ development significantly affects the pace of these changes

Coverage Bias in European Telephone Surveys: Developments of Landline and Mobile Phone Coverage across Countries and over Time

With the decrease of landline phones in the last decade, telephone survey methodologists face a new challenge to overcome coverage bias. In this study we investigate coverage error for telephone surveys in Europe over time and compare two situations: classical surveys that rely on landline only with surveys that also include mobile phones. We analyzed Eurobarometer data, which are collected by means of face-to-face interviews and contain information on ownership of landline and mobile phones. We show that for the period 2000-2009, time has a significant effect on both mobile phone penetration and coverage bias. In addition, the countries’ development significantly affects the pace of these changes