To account for
the issue of selection bias and the potentially unobserved parent characteristics as the possible reason choice students appear to perform better in my first comparison, I next also accounted for the parent - related variables.
In order to circumvent
the issue of selection bias in the case of mandatory retention policies like the one proposed for Michigan, recent studies have utilized a statistical approach that compares children who fall just above and just below the cutoff used to determine retention.
Not exact matches
We carefully studied
issues raised by skeptics:
biases from urban heating (we duplicated our results using rural data alone), from data
selection (prior groups selected fewer than 20 percent
of the available temperature stations; we used virtually 100 percent), from poor station quality (we separately analyzed good stations and poor ones) and from human intervention and data adjustment (our work is completely automated and hands - off).
All fair as far as it goes, although readers who want to dig into the controversies around
selection bias, methodological research
issues, or a final reckoning
of impact will be disappointed.
Key
issues identified in inland and marine presentations included the need to standardize the spatial domain, minimize double counting
of emissions from lakes and wetlands, reduce
bias in field site
selections, improve measurements
of cold season emissions, and improve scaling
of hot spots.
We carefully studied
issues raised by skeptics:
biases from urban heating (we duplicated our results using rural data alone), from data
selection (prior groups selected fewer than 20 percent
of the available temperature stations; we used virtually 100 percent), from poor station quality (we separately analyzed good stations and poor ones) and from human intervention and data adjustment (our work is completely automated and hands - off).
In partnership with researchers from related projects in Canada, the UK, South Australia, the Northern Territory and Western Australia, Aboriginal organisations and policymakers, we will analyse whole -
of - population data for New South Wales (NSW) to investigate the determinants
of positive early childhood development in Aboriginal children, and assess the impacts
of two «real - world» programmes that were implemented under circumstances where evidence
of their efficacy was unable to be derived from RCTs: the NSW Aboriginal and Maternal Infant Health Service (AMIHS) 45 and the NSW Department
of Family and Community Services (FACS) Brighter Futures Program.46 Early evaluations
of these programmes suggested some positive changes in proximal outcomes related to their objectives.45, 47, 48 However, each
of these evaluations was limited by one or more
of the following: use
of single data sets, less than 2 years
of outcome data and / or
issues of confounding and
selection bias.
Another
issue that might limit enthusiasm for the findings is that the majority
of studies were affected by a
selection bias.