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CPH Exam - Biostatistics

Terms in this set (410)

(Syn: therapeutic trial) A research activity that involves the administration of a test regimen to humans to evaluate its efficacy and safety. The term is subject to wide variation in usage, from the first use in humans without any control treatment to a rigorously designed and executed experiment involving test and control treatments and randomization. Several phases of clinical trials are distinguished:
Phase I trial Safety and pharmacologic profiles. The first introduction of a candidate vaccine or a drug into a human population to determine its safety and mode of action. In drug trials, this phase may include studies of dose and route of administration. Phase I trials usually involve fewer than 100 healthy volunteers. Phase II trial Pilot efficacy studies. Initial trial to examine efficacy usually in 200 to 500 volunteers; with vaccines, the focus is on immunogenicity, and with drugs, on demonstration of safety and efficacy in comparison to other existing regimens. Usually but not always, subjects are randomly allocated to study and control groups. Phase III trial Extensive clinical trial. This phase is intended for complete assessment of safety and efficacy. It involves larger numbers, perhaps thousands, of volunteers, usually with random allocation to study and control groups, and may be a multicenter trial. Phase IV trial With drugs, this phase is conducted after the national drug registration authority (e.g., the Food and Drug Administration in the United States) has approved the drug for distribution or marketing. Phase IV trials may include research designed to explore a specific pharmacologic effect, to establish the incident of adverse reactions, or to determine the effects of long-term use. Ethical review is required for phase IV clinical trials, but not for routine post marketing surveillance.
a selected subset of a population. A sample may be random or nonrandom and may be representative or nonrepresentative. Several types of samples exist:area sample - a method of sampling that can be used when the numbers in the population are unknown. The total area to be sampled is divided into subareas, e.g. by means of a grid that produces squares on a map; these subareas are then numbered and sampled, using a table of random numbers.
cluster sample - each unit selected is a group of persons (all persons in a city block, a family, a school, etc.) rather than an individual.
grab sample (sample of convenience) - samples selected by easily employed but basically nonprobabilistic methods. It is improper to generalize from the results of a survey based upon such a sample, for there is no way of knowing what types of bias may have been present.
probability (random) sample -all individuals have a known chance of selection. They may all have an equal chance of being selected, or, if a stratified sampling method is used, the rate at which individuals from several subsets are sampled can be varied so as to produce greater representation of some classes than others.
simple random sample - a form of sampling design in which n distinct units are selected from the N units in the population in such a way that every possible combination of n units is equally likely to be the sample selected. With this type of sampling design the probability that the ith population unit is included in the same, so that theinclusion probability is the same for each unit. Designs other than this one may also give each unit equal probability of being included, both other here does each possible sample of n units have the same probability.
stratified random sample - this involves dividing the population into distinct subgroups according to some important characteristic, such as age or socioeconomic status, and selecting a random sample out of each subgroup. If the proportion of the sample drawn from each of the subgroups or strata, is the same as the proportion of the total population contained in each stratum, then all strata will be fairly represented with regard to numbers of persons in the sample.
systematic sample - the procedure of selecting according to some simple, systematic rule, such as all persons whose names begin with specified alphabetic letters, born on certain dates, or located at specified points on a list. A systematic sample may lead to errors that invalidate generalizations.
A series of methods for selecting 'good' (although not necessarily the best) subsets of explanatory variables when using regression analysis. The three most commonly used of these methods are forward selection, backward elimination and a combination of both of these known asstepwise regression. The criterion used for assessing whether or not a variable should be added to an existing model in forward selection or removed from an existing model in backward elimination is, essentially, the change in the residual sum-of-squares produced by the inclusion or exclusion of the variable. Specifically, in forward selection, an 'F-statistic' known as the F-to-enter is calculated as:

and compared with a preset term; calculated Fs greater than the preset value lead to the variable under consideration being added to the model. (RSSm and RSSm+1 are the residual sums of squares when models with m and m + 1 explanatory variables have been fitted.) In backward selection a calculated F less than a corresponding F-to-remove leads to a variable being removed from the current model. In the stepwise procedure, variables are entered as with forward selection, but after each addition of a new variable, those variables currently in the model are considered for removal by the backward elimination process. In this way it is possible that variables included at some earlier stage might later be removed, because the presence of new variables has made their contribution to the regression model no longer important. It should be stressed that none of these automatic procedures for selecting variables is foolproof and they must be used with care.