Error in Epidemiologic Research Lecture 1 PDF

Error in Epidemiologic Research Dr. Muhammad Ahmed Alshyyab Lecture 1 CHAPTER 9 LEARNING OBJECTIVES: In this lecture, you will be able to demonstrate the following key massages: To define the random error and systematic error and differentia...

Error in Epidemiologic Research Dr. Muhammad Ahmed Alshyyab Lecture 1 CHAPTER 9 LEARNING OBJECTIVES: In this lecture, you will be able to demonstrate the following key massages: To define the random error and systematic error and differentiate between them To understand and describe parameters and estimates and differentiate between them To understand the random error (imprecision) and it is relation with probability To understand the concept of probability and it is application in the epidemiological studies.  Errors in epidemiological studies 1. Random error and systematic error 2. Parameters and Estimates Errors in epidemiological studies Precision refers to the spread of a set of results measurements are precise when there is less scatter in the results Scatter is a measurement of how close the values are to each other in a set of data Accuracy refers to how close the measurements are to the true value True value is the accepted or agreed or nominal value, basically the true value is what the actual value is or what the value should be Measurements errors Target Analogy (a metaphor) These results are free from both random and systematic errors (Figure a). These results are free from systematic error but are affected by random error(Figure b). Target Analogy The results will be consistently off-centre (Figure c). These shots are free from random error but are affected by systematic error. Results distribute themselves randomly and systematic error is present (Figure d). Systematic errors Vs Random Parameters and estimates Parameter; refer to the error-free value of the epidemiologic measure. Although parameters are objective characteristics of the population being studied, they are impossible to observe (calculate) directly. An imperfect estimate of the parameter based on the data from a study. This imperfect estimate is prone to both random and systematic errors. Target Analogy will represent a measure of association estimate from a particular study. MA will represent the (error-free) measure of association parameter.  The random and systematic errors inherent in an estimate bring the value of the estimate away from or toward the true value of the parameter. For example, an observed (calculated) risk ratio estimate of 3 might represent an overestimate of the risk ratio parameter by 1 with random error shifting the estimate up by 0.25 and systematic error shifting it up by an additional 0.75. Although the amount of random error can be estimated from the data in the form of a standard error (or variance), the amount of systematic error cannot be easily quantified. Because random error and systematic error represent different types of problems with different types of solutions, they will be addressed separately. Random error (imprecision); Probability Random error is governed by the laws of probability. The probability is changed based on our limited ability to predict its outcome. Probabilities are defined in terms of the variability in the data that cannot otherwise be explained. This second view of probability has relevance when studying disease occurrence. Thus, the objective state of affairs has not changed but the revised probability has changed because our knowledge about underlying conditions is now different. This revised probability conveys the extent to which we now believe the event is likely to occur.