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'I'm going to live forever': the guarantee-time bias
Some study findings are more probably due to a bias in terms of who is included in the studies than to the miraculous effects of occupation, winning awards, or ER status, or whatever is being studied. How should investigators go about avoiding this bias, and more specifically, what should readers look for when they’re reading about some new miracle cure?
Click on the PDF icon above to read the full article.
Some study findings are more probably due to a bias in terms of who is included in the studies than to the miraculous effects of occupation, winning awards, or ER status, or whatever is being studied. How should investigators go about avoiding this bias, and more specifically, what should readers look for when they’re reading about some new miracle cure?
Click on the PDF icon above to read the full article.
Some study findings are more probably due to a bias in terms of who is included in the studies than to the miraculous effects of occupation, winning awards, or ER status, or whatever is being studied. How should investigators go about avoiding this bias, and more specifically, what should readers look for when they’re reading about some new miracle cure?
Click on the PDF icon above to read the full article.
Size, follow-up, data analysis—good; post hoc analysis, interpretation—not so much
It’s easy to know whether a critique of some article or other was written by a statistician or a methodologist—it states how badly the study was done and how incompetently the data were analyzed. Indeed, it is extremely easy to criticize any study, no matter how well it was conducted, because all applied research involves compromises of one sort or another. Well, be prepared for a surprise. In this column, we will be discussing a study that we believe was carried out well and analyzed correctly. That’s not to say that we agree with their conclusions (we don’t), but at least the study yields data that people can argue about without dismissing the paper as a whole.
Click on the PDF icon at the top of this introduction to read the full article.
It’s easy to know whether a critique of some article or other was written by a statistician or a methodologist—it states how badly the study was done and how incompetently the data were analyzed. Indeed, it is extremely easy to criticize any study, no matter how well it was conducted, because all applied research involves compromises of one sort or another. Well, be prepared for a surprise. In this column, we will be discussing a study that we believe was carried out well and analyzed correctly. That’s not to say that we agree with their conclusions (we don’t), but at least the study yields data that people can argue about without dismissing the paper as a whole.
Click on the PDF icon at the top of this introduction to read the full article.
It’s easy to know whether a critique of some article or other was written by a statistician or a methodologist—it states how badly the study was done and how incompetently the data were analyzed. Indeed, it is extremely easy to criticize any study, no matter how well it was conducted, because all applied research involves compromises of one sort or another. Well, be prepared for a surprise. In this column, we will be discussing a study that we believe was carried out well and analyzed correctly. That’s not to say that we agree with their conclusions (we don’t), but at least the study yields data that people can argue about without dismissing the paper as a whole.
Click on the PDF icon at the top of this introduction to read the full article.