That BLUP is a Good Thing: The Estimation of Random Effects

Robinson, Gwen

doi:10.1214/ss/1177011926

Cited by 1,420 publications

(1,002 citation statements)

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“…the extended basis function Z needs to be constrained in some way. Following Ruppert et al (2003), based on earlier work by Robinson (1991) and Brumback et al (1999) …”

Section: Resultsmentioning

confidence: 99%

Driven to drink: Sin taxes near a border

Beatty

Larsen

Sommervoll

2009

Journal of Health Economics

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Abstract:This paper investigates household purchasing behavior in response to differing alcohol and tobacco taxes near an international border. Our study suggests that large tax differentials near borders induce economically important tax avoidance behavior that may limit a government's ability to raise revenue and potentially undermine the pursuit of important health and social policy goals. We match novel supermarket scanner and consumer expenditure data to measure the size and scope of the effect for households and stores. We find that stores near/far from the international border have statistically significantly lower/higher sales of beer and tobacco than comparable stores far/near the border. Moreover, we find that households near the border report higher consumption of these same goods. This is consistent with households facing lower prices. Finally, we find measures of externalities associated with the consumption of alcohol and tobacco are higher near the border.

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“…the extended basis function Z needs to be constrained in some way. Following Ruppert et al (2003), based on earlier work by Robinson (1991) and Brumback et al (1999) …”

Section: Resultsmentioning

confidence: 99%

Driven to drink: Sin taxes near a border

Beatty

Larsen

Sommervoll

2009

Journal of Health Economics

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“…Third, our real-time biofeedback system enabled the successful implementation of specific trunk lean magnitudes (34). Finally, the linear mixed model statistical method is considered more powerful than regression analysis or repeated-measures ANOVA (37,44). The approach allowed consideration of random variability attributed to participants and the inclusion of all data points.…”

Section: Discussionmentioning

confidence: 99%

Trunk lean gait modification and knee joint load in people with medial knee osteoarthritis: The effect of varying trunk lean angles

Simić¹,

Hunt²,

Bennell³

et al. 2012

Arthritis Care & Research

104

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Objective. To evaluate whether increased lateral trunk lean toward the symptomatic lower extremity during gait in people with medial knee osteoarthritis (OA) immediately alters symptoms or medial knee load, as measured by the external knee adduction moment (KAM). Methods. Participants with medial knee OA (n ‫؍‬ 22) underwent 3-dimensional gait analysis to measure KAM peaks (early and late stance) and KAM impulse. Following the analysis of natural gait, participants were trained to lean their trunk toward the symptomatic leg during ipsilateral stance over 3 randomly ordered conditions (6°, 9°, and 12°lean). A projection screen displayed real-time trunk angles and target levels. Pain/discomfort in the knees, the hip, and the back were measured across conditions. Load-modifying effects of increasing lean magnitudes were investigated using linear mixed models. Mediating effects of peak lean timing and participant characteristics (pain and malalignment) were evaluated. Results. Increased trunk lean reduced all KAM measures (P

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“…* When turning to estimation details (including the choice of method in evaluating the variance of the error term), we decided to rely on the standard least-squares-related methods. The reason for this is that in the case of our dataset it is rather hard to justify the need for using an approach based on linear unbiased prediction [34]. ** One should also bear in mind that in the case of samples as small as the one used in this paper, several problems occur during the estimation of panel models for variables in their levels.…”

Section: Methodsologymentioning

confidence: 99%