This reminds me of the time I mixed uncorrected radiocarbon dates with corrected ones, and got a bit skewed distribution of volcanic events, though I tried to correct
for observational bias on earlier and smaller eruptions.
We estimate that ~ 35 % of KOIs are false positives due to contamination, when performing a first - order correction
for observational bias.
Not exact matches
Although reanalysis of the available evidence is important, the ability to properly control
for bias and confounding [factors that can influence outcomes] in
observational studies is often limited, and without randomized controlled trials specifically designed to test the hypothesis, the issue of nonspecific effects of vaccines may remain subject to continuing debate.»
The results in Table 10 support the notion that the
observational study design does a good job of controlling
for selection
bias in the evaluation of charter effects (or that there is not much selection
bias in the first place).
Because value - added measures adjust
for the characteristics of students in a given classroom, they are less
biased measures of teacher performance than are unadjusted test score measures, and they may be less
biased even than some
observational measures.
This is especially important when
observational (and value - added) data are to be used
for high - stakes accountability systems in that the data yielded via really both measurement systems may be less likely to reflect «true» teaching effectiveness due to «true»
bias.
She used R (i.e., a free software environment
for statistical computing and graphics) to simulate correlation scatterplots (see Figures below) to illustrate three unique situations: (1) a simulation where there are two indicators (e.g., teacher value - added and
observational estimates plotted on the x and y axes) that have a correlation of r = 0.28 (the highest correlation coefficient at issue in the aforementioned post); (2) a simulation exploring the impact of negative
bias and a moderate correlation on a group of teachers; and (3) another simulation with two indicators that have a non-linear relationship possibly induced or caused by
bias.
This is true not only
for stability, but also
for issues of
bias (another claim commonly leveled against VAMs that may well apply to
observational and student survey measures).
Although I've not been able to find enough to get a broad view of the Arctic, and some data such as Buoys suffers from an
observational bias — more substantial floes of ice are chose
for the placement of buoys.
Accounting
for the considerable disagreement among satellite - era
observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow cover over the Canadian land mass, reflecting a broader Northern Hemisphere positive
bias.
Po Chedley say: «The apparent model -
observational difference
for tropical upper tropospheric warming represents an important problem, but it is not clear whether the difference is a result of common
biases in GCMs,
biases in
observational datasets, or both.»
Finally, unlike precipitation,
for which long and reliable historical records exist in some parts of the world, records
for other aspects of weather are too short to detect trends or contain
observational biases that render trends meaningless.
The scenario encapsulates so much BS from assumptions, ignorance of
observational trends, rational action on big and apparent dangers, and then there is the data sets, the models, the potential
for bias, did I mention the assumptions.
... But by placing the null hypothesis in a priviledged position from which it can only be dislodged by a mountain of
observational evidence, this approach provides a strong inbuilt
bias for the status quo which can not be justified on any rational decision - theoretic grounds.»
Moreover, while there are other variants, we have this
observational record
for the complete area and we don't have to worry about sampling
bias and homogenization.
An understudied yet crucial source of measurement variance within
observational tools is whether the «gold standard» ratings that account
for whether a trained rater passes certification of reliability has cultural
biases that would unfairly privilege some groups of people with certain cultural vantage points over others.