Ebook Veterinary epidemiology (4/E): Part 2
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Ebook Veterinary epidemiology (4/E): Part 2
38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2order to aid decision making. In an ideal world each research question would be addressed by a particular study, the study would provide an exact representation of the relevant domain, and the study results would provide the information needed to truthfully answer the question. Unfortunately, this i Ebook Veterinary epidemiology (4/E): Part 2s never the case. In truth, all studies provide flawed depictions of‘reality’. Maclure and Schneeweiss (2001) imagine epidemiological studies of causaEbook Veterinary epidemiology (4/E): Part 2
tion to be like a telescope used to observe populations they call this the Episcope. The Episcope is made up of a number of filters and lenses, each o38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2n in Figure 18.1. This has eight lenses representing the key issues affecting the validity of epidemiological studies (although these could be thought of as compound lenses, each containing an array of imperfect lenses):1background factors;2interpretation biases;3selection biases;4statistical intera Ebook Veterinary epidemiology (4/E): Part 2ction and effect-measure modification;5information biases;6confounding;7errors in analysis;8communication biases.Each of these lenses will induce an aEbook Veterinary epidemiology (4/E): Part 2
mount of error and the resulting image of reality will be imperfect. An unavoidable problem is that we can only compare this image with other imperfec38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2 the error associated with each of these lenses as best as possible and then to understand where residual errors remain and the potential impact of these on the results. By doing this we can get closerto knowing the true situation. Although it is often useful to think about these main sources of err Ebook Veterinary epidemiology (4/E): Part 2or in isolation, in reality they are an interconnected complex that may independently impact estimates of association between an exposure and an outcoEbook Veterinary epidemiology (4/E): Part 2
me, but also may do so by impacting one another. Hence, information biases may lead to selection biases and may affect measurement of, and therefore t38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2belief, conclusion or action that is not correct. In epidemiology, the term error may be used in numerous ways. It is common to distinguish between random error (Box 18.1) and nonrandom error. Random error is variation that is due to chance. That is. random errors in one variable are not associated Ebook Veterinary epidemiology (4/E): Part 2with other variables. In contrast nonrandom errors vary systematically between groups and are often called biases. (The concept of bias was introducedEbook Veterinary epidemiology (4/E): Part 2
in Chapters 10 and 15.) Hence, bias occurs when an error affects some groups more than others. The term bias, when used in epidemiology, does not nec38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2xtent, on one's worldview. Some people view chance variation as an intrinsic part of reality that prevents full prediction, whilst others take a more deterministic view in which full understanding of all relevant variables can enable prediction without error, with random error simply resulting from Ebook Veterinary epidemiology (4/E): Part 2incomplete knowledge. However, even with this latter view, in most situations it is unlikely that we will acquire sufficient knowledge to enable fullEbook Veterinary epidemiology (4/E): Part 2
prediction, and the unpredictability that results from incomplete knowledge has the same effect as that due to random variation.Veterinary Epidemiotci38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 24 18 VaMiry in epide/iw>taj>cứf ỊtudieíFig. 18.1 Madure and Schneewe«$s (2001) imagine epidemiological studies of causation to be like a telescope (an Episcope) made up of imperfect lenses. The observer (epidemiologist) makes observations through this series of lenses, within each of whit h particul Ebook Veterinary epidemiology (4/E): Part 2ar bases arxJ errors rnay or c ur.Box 18.1 An example of random error, selection bias and information bias.A survey is carried out lo assess (he prevaEbook Veterinary epidemiology (4/E): Part 2
lence of lameness in a dairy herd of 100 milking cows. Because of time constraints, only a sample of the herd can be examined. If the entire herd were38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2ine a random sample of 10 cows, we may expect to find one lame. This last statement implies that, if we took many random samples of 10 cows, the average number of lame cows observed in the samples would be one.Imagine a veterinarian examines a random sample of 20 cows from this herd and finds four l Ebook Veterinary epidemiology (4/E): Part 2ame; the prevalence estimate is therefore 20%. If another survey v/as conducted choosing another random sample of 20 animals. the prevalence estimateEbook Veterinary epidemiology (4/E): Part 2
may have been 5%. If the study IS repeated many times, the average prevalence estimate will be very similar to the true prevalence. The differences in38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2r. The larger the sample size, the lower the error and die more precise die estimate of prevalence.However, this assumes there is no systematic error (bias) in lameness assessment. Selection bias may have occurred if die cows selected were the first 20 to enter the yard. This method of selection may Ebook Veterinary epidemiology (4/E): Part 2 underestimate the prevalence of lameness, as the lame cows may tend to be toward the back of the herd. Importantly, repeat ing the study, with the saEbook Veterinary epidemiology (4/E): Part 2
me selection procedure, would lead to similarly biased estimates of the prevalence of lameness, with some variation due to random error.There may also38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2derestimated. Alternatively, the inspection may be carried out on very rough ground, resulting in the overdiagnosis of lameness and an overestimation of the prevalence. Again, repeating the study under these same circumstances would lead to repeated estimation of biased prevalence estimates.T he res Ebook Veterinary epidemiology (4/E): Part 2ults or interpretation of an epidemiological stud)- may, therefore, be 'wrong' due to random error (chance) and systematic error (bias). When conductiEbook Veterinary epidemiology (4/E): Part 2
ng studies, epidemiologists should attempt to reduce both sources of error. When interpreting studies, a reader should, ideally, be aware of both type38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2uracy, precision and validity in epidemiological studiesThe terms accuracy, precision and validity are often applied to measurements (see Chapter 10). However,these terms can equally be applied to epidemiological studies. A study that is able to estimate a parameter (e.g., prevalence or relative ris Ebook Veterinary epidemiology (4/E): Part 2k) with little error is said to have a high level of accuracy. In such cases the para meter estimates will be close approximations of the true values.Ebook Veterinary epidemiology (4/E): Part 2
Just like error, accuracy can be divided into two component parts. Studies in which parameters are estimated with little random error are said to hav38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2rate, it must he both precise and valid.Validity may further divided in to two types: internal validity and external validity (see Chapter 17). A study is said to be internally valid if the study results provide unbiased information about rhe individuals included in the study (i.e., the study sample Ebook Veterinary epidemiology (4/E): Part 2 orFig. 18 J Schematic representation of the process of selection of the sample available to the analyst from the target. At each stage only a sub setEbook Veterinary epidemiology (4/E): Part 2
may proceed to the subsequent stage. The aim of the selection process should be to ensure that all study units present at higher levels have equal pr38318Validity in epidemiological studiesThe goal of epidemiology is to generate and interpret information about disease and health in populations in o Ebook Veterinary epidemiology (4/E): Part 2h of the practice of epidemiology is concerned with minimizing bias in order to maximize internal validity. External validity refers to the ability to extrapolate from the results of a study to a target population. In designing a study there may be tension between attempts to maximize internal valid Ebook Veterinary epidemiology (4/E): Part 2ity and external validity. Selection of a relatively narrow study population may increase the potential to sample representatively from that populatioEbook Veterinary epidemiology (4/E): Part 2
n, but may make the study population unrepresentative of the target population. Although such situations may not be ideal, internal validity should heGọi ngay
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