Ch 10 Data Interpretation Issues Internal Validity There have been proper selection of study groups There is a lack of error in measurement Concerned with appropriate o Measure of exposure o Measure of outcome o Association between exposure disease External validity Sources of Error Random Errors Implies the ability to generalize beyond a set of observations to come universal statement o Fluctuations around a true value of a parameter because of sampling variability o Poor precision Factor being measured is not measured sharply Analogous to aiming a rifle at a target that is not in focus Precision can be increased by increasing sample size or the number of measurements o Sampling Error Sample is not representative of target population Increasing the sample size can reduce sampling error o Variability in Measurement Lack of agreement in results from time to time reflects random error inherent in the type of measurement procedure employed Systematic Errors Bias o Deviation of results from the truth or processes leading to such deviation o Selection bias When the relation between exposure and disease is different for those who participate and those who theoretically would be eligible for study but do not participate To reduce Develop an explicit case definition Enroll all cases in a defined time region Strive for high participation rates Take precautions to ensure representativeness o Information bias Can be introduced as a result of measurement error in assessment of both exposure and disease Recall bias better recall among cases than among controls Interviewer abstractor bias occurs when interviewers probe more thoroughly for an exposure in a case than in a control Prevarication lying bias occurs when participants have ulterior motives for answering a question and thus may underestimate or exaggerate an exposure To reduce Blind interviewers as to subjects study status Provide standardized training sessions and protocols Use standardized data collection forms o Confounding Blind participants as to study goals and class status Distortion of the estimate of the effect of an exposure of interest because it is mixed with the effect of an extraneous factor Occurs when a crude and adjusted measures of effect are not equal difference of at least 10 Can be controlled for in the data analysis Criteria Be a risk factor for the disease Be associated with the exposure Not be an intermediate step in the causal path b n exposure disease