What is the control group in a research study?
The control group consists of participants who do not receive the experimental treatment being studied. Instead, they get a placebo (a fake treatment; for example, a sugar pill); a standard, nonexperimental treatment (such as vitamin C, in the zinc study); or no treatment at all, depending on the situation.
What is the difference between the treatment group and control group?
The treatment group consists of participants who receive the experimental treatment whose effect is being studied (in this case, zinc tablets). The control group consists of participants who do not receive the experimental treatment being studied.
What did the research team conclude about the new drug?
The research team concluded that the new drug is effective in relieving pain. Is this conclusion well justified? Explain. a. Randomized b. Since, the experiment is a randomized one, the conclusion is well justified A medical researcher wants to determine whether exercising can lower blood pressure.
Is one in which the assignment to treatment groups is not made by the investigator?
Scientists observe differences in health outcomes between the groups of smokers and nonsmokers. Because the assignment of treatments (smoking or nonsmoking) is not made by the investigators, this is an observational study.
What is a sample that is not drawn by a well-defined random method?
simple random sample. sample chosen by a method in which each collection of "n" population items is equally likely to be apart of the sample (lottery) samples of convenience. sample that is not drawn by a well defined random method (may differ systematically in some way from the population) stratified random sample.
What sample is one in which the population is divided into groups and a random sample of groups is drawn?
In a cluster sample, the population is divided into groups, and a random sample from each group is drawn.
Is a sample chosen by a method in which each collection of items of the same size from the population is equally likely to make up the sample?
a number that describes a sample. of size n is a sample chosen by a method in which each collection of n population items is equally likely to comprise the sample. It is analogous to the lottery. In cluster sampling, items are drawn from the population in groups.
What is systematic random sampling?
Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling.
What is the difference between simple random sampling and systematic random sampling?
Simple random sampling requires that each element of the population be separately identified and selected, while systematic sampling relies on a sampling interval rule to select all individuals.
What is cluster sampling vs stratified sampling?
In Cluster Sampling, the sampling is done on a population of clusters therefore, cluster/group is considered a sampling unit. In Stratified Sampling, elements within each stratum are sampled. In Cluster Sampling, only selected clusters are sampled. In Stratified Sampling, from each stratum, a random sample is selected.
Which sampling method divides the population up into sections randomly selects some of those sections then chooses all the members from the selected sections to study?
Cluster samplingCluster sampling divides the population into groups, then takes a random sample from each cluster.
What is cluster random sampling?
Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample. The clusters should ideally each be mini-representations of the population as a whole.
What is a representative study?
A representative sample is a subset of a population that seeks to accurately reflect the characteristics of the larger group. For example, a classroom of 30 students with 15 males and 15 females could generate a representative sample that might include six students: three males and three females.
What is stratified sampling in research?
In stratified sampling, researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment, etc). Once divided, each subgroup is randomly sampled using another probability sampling method.
What is sampling and types of sampling?
There are two types of sampling methods: Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group. Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.
What is nonrandomized treatment allocation?
Treatment allocation in a clinical trial can be randomized or nonrandomized. Nonrandomized schemes, such as investigator-selected treatment assignments, are susceptible to large biases. Even nonrandomized schemes that are systematic, such as alternating treatments, are susceptible to discovery and could lead to bias. Obviously, to reduce biases, we prefer randomized schemes. Credibility requires that the allocation process be non-discoverable. The investigator should not know what the treatment will be assigned until the patient has been determined as eligible. Even using envelopes with the treatment assignment sealed inside is prone to discovery.
What is the term for a constrained randomization?
Another type of constrained randomization is called stratified randomization. Stratified randomization refers to the situation in which strata are constructed based on values of prognostic variables and a randomization scheme is performed separately within each stratum. For example, suppose that there are two prognostic variables, age and gender, such that four strata are constructed:
What is minimization in randomization?
Minimization is another, rather complicated type of adaptive randomization. Minimization schemes construct measures of imbalance for each treatment when an eligible patient is ready for randomization. The patient is assigned to the treatment which yields the lowest imbalance score. If the imbalance scores are all equal, then that patient is randomly assigned a treatment. This type of adaptive randomization imposes tight control of balance, but it is more labor-intensive to implement because the imbalance scores must be calculated with each new patient. Some researchers have developed web-based applications and automated 24-hour telephone services that solicit information about the stratifiers and a computer algorithm uses the data to determine the randomization
What is adaptive randomization?
Adaptive randomization refers to any scheme in which the probability of treatment assignment changes according to assigned treatments of patients already in the trial. Although permuted blocks can be considered as such a scheme, adaptive randomization is a more general concept in which treatment assignment probabilities are adjusted.