The authorsà refusal to answer questions regarding
the statistical validity of the model or to provide the model statistics and data add to the doubts about the theory.
Not exact matches
Sufficient information should be supplied to allow readers to judge whether any assumptions necessary for the
validity of statistical approaches (e.g., data are normally distributed, survival data are consistent with proportional hazards in a Cox regression
model) have been verified.
Finally, researchers discourage the use
of value - added
modeling in teacher evaluation practices due to their low levels
of statistical reliability across years and limited
validity for detecting individual teacher effects (Darling - Hammond, 2012).
Summary
of how they got to this finding: They use CMIP
models which, if not outright flawed, have not proved their
validity in estimated temperature levels in the 2030 to 2070 timeframe, are used as the basis for extrapolations that assert the creation
of more and more 3 - sigma «extreme events»
of hot weather; this is despite the
statistical contradiction and weak support for predicting significant increases in outlier events based on mean increases; then, based on
statistical correlations between mortality and extreme heat events (ie heat waves), temperature warming trends are conjured into an enlargement
of the risks from heat events; risks increase significantly only by ignoring obvious adjustments and mitigations any reasonable community or person would make to adapt to warmer weather.
I've previously drawn attention to this need to ensure
validity of statistical inference as a reason why climate
modelling is not immune from these findings, but some here continue to seek refuge in the first point above i.e. this can't be right because it is inconsistent with the science.
Novel latent
statistical models of child adversity, depression, anxiety, and psychotic experiences were produced, with concurrent and prospective
validity.