A recent paper by Philip A. Schrodt (PSU--Poli Sci), Seven Deadly Sins of Contemporary Quantitative Political Analysis, identifies the following sins:
1. Kitchen sink models that ignore the effects of collinearity;
2. Pre-scientific explanation in the absence of prediction;
3. Reanalyzing the same data sets until they scream;
4. Using complex methods without understanding the underlying assumptions;
5. Interpreting frequentist statistics as if they were Bayesian;
6. Linear statistical monoculture at the expense of alternative structures;
7. Confusing statistical controls and experimental controls.
The paper argues:
"A combination of technological change, methodological drift and a certain degree of intellectual sloth and sloppiness, particularly with respect to philosophy of science, has allowed contemporary quantitative political methodology to accumulate a series of highly dysfunctional habits that have rendered a great deal of contemporary research more or less scientifically useless. The cure for this is not to reject quantitative methods|and the cure is most certainly not a postmodernist nihilistic rejection of all systematic method|but rather to return to some fundamentals, and take on some hard problems rather than expecting to advance knowledge solely through the ever increasing application of fast-twitch muscle fibers to computer mice." The paper closes with the observation that "[t]he answer to these problems is solid, thoughtful, original work driven by an appreciation of both theory and data. Not postmodernism."