El Registro de Gemelos de Murcia. Un recurso para la investigación sobre conductas relacionadas con la salud

Genetically informative designs and, in particular, twin studies, are the most widely used methodology to analyse the relative contribution of genetic and environmental factors to inter-individual variability. These studies basically compare the degree of phenotypical similarity between monozygotic and dizygotic twin pairs. In addition to the traditional estimate of heritability, this kind of registry enables a wide variety of analyses which are unique due to the characteristics of the sample. The Murcia Twin Registry is population-based and focused on the analysis of health-related behaviour. The observed prevalence of health problems is comparable to that of other regional and national reference samples, which guarantees its representativeness. Overall, the characteristics of the Registry facilitate developing various types of research as well as genetically informative designs, and collaboration with different initiatives and consortia.     

Estimating transmitted power density from mobile phone: an epidemiological pilot study with a software modified phone

The aims of this study were to evaluate the weekly and annual cumulative radiofrequency-electromagnetic field (RF-EMF) exposure attributed to mobile phone (MP) use, and assess whether a novel app (Quanta Monitor?) could be employed in a small human sample to characterise the RF-EMF exposures associated with the use of MPs. Ten participants provided their two months’ daily objective data on their MP exposures (i.e. transmitted and received power densities) attributed to different modes of MP usage such as cellular calls, cellular data and Wi-Fi. The results demonstrated that total transmitted power density (cellular phone calls, data and Wi-Fi surfing) could be many orders of magnitude higher than that from the total received power density. Of the total transmitted power density, cellular data use contributed the largest portion. Our study showed that Quanta Monitor? could be employed in prospective assessment of exposures to MPs in epidemiological studies.     

Measurement invariance,the lack thereof,and modeling change

Purpose

Measurement invariance issues should be considered during test construction. In this paper, we provide a conceptual overview of measurement invariance and describe how the concept is implemented in several different statistical approaches. Typical applications look for invariance over things such as mode of administration (paper and pencil vs. computer based), language/translation, age, time, and gender, to cite just a few examples. To the extent that the relationships between items and constructs are stable/invariant, we can be more confident in score interpretations.

Methods

A series of simulated examples are reported which highlight different kinds of non-invariance, the impact it can have, and the effect of appropriately modeling a lack of invariance. One example focuses on the longitudinal context, where measurement invariance is critical to understanding trends over time. Software syntax is provided to help researchers apply these models with their own data.

Results

The simulation studies demonstrate the negative impact an erroneous assumption of invariance may have on scores and substantive conclusions drawn from naively analyzing those scores.

Conclusions

Measurement invariance implies that the links between the items and the construct of interest are invariant over some domain, grouping, or classification. Examining a new or existing test for measurement invariance should be part of any test construction/implementation plan. In addition to reviewing implications of the simulation study results, we also provide a discussion of the limitations of current approaches and areas in need of additional research.