"The design of experiments (DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation."
A research design that involves manipulating one or more variables to determine their effect on another variable.
Research Design: This topic discusses the different types of research designs and how to choose the right one for a study. It covers experimental designs, quasi-experimental designs, and non-experimental designs.
Randomization: This topic focuses on the principles of randomization, including random assignment and random sampling. It discusses the importance of randomization in ensuring unbiased results.
Causality: This topic discusses the concept of causality in experiments and how to establish causality. It covers the criteria for causality, including temporal precedence, covariation, and non-spuriousness.
Hypothesis Testing: This topic covers the basics of hypothesis testing, including null and alternative hypotheses, statistical significance, and type I and type II errors. It discusses how to test hypotheses in experiments.
Sampling: This topic discusses the different types of sampling techniques, including random sampling, stratified sampling, and cluster sampling. It covers the advantages and disadvantages of each technique.
Controls: This topic covers the concept of controls in experiments, including placebo controls, double-blinded controls, and crossover controls. It discusses how to use controls to isolate the effects of an independent variable.
Data Analysis: This topic covers the basics of data analysis, including descriptive statistics, inferential statistics, and regression analysis. It discusses how to analyze data from experiments.
Ethics: This topic discusses the ethical considerations in conducting experiments, including informed consent, privacy, and confidentiality. It discusses the role of institutional review boards in ensuring ethical research practices.
External Validity: This topic covers the concept of external validity in experiments, including generalizability and replication. It discusses how to ensure the results of an experiment can be applied to a larger population.
Internal Validity: This topic covers the concept of internal validity in experiments, including selection bias, measurement bias, and maturation. It discusses how to control for these factors in an experiment to ensure accurate results.
Survey Experiments: Conducted through survey questionnaires to measure the effects of various interventions or treatments, such as manipulating the wording of questions or presenting different information.
Field Experiments: Conducted in a natural or real-world setting, such as a political campaign, to measure the effects of interventions or treatments.
Lab Experiments: Conducted in a controlled environment, such as a laboratory, to measure the effects of interventions or treatments.
Natural Experiments: Naturally occurring events that create variations in the independent variable, allowing for the measurement of the effects of the intervention or treatment.
Quasi Experiments: Similar to natural experiments, but the researcher manipulates the independent variable to induce variations in the dependent variable.
Randomized Control Trials: Experimental design where participants are assigned randomly to either a treatment or control group to measure the effect of an intervention or treatment.
Comparative Experiments: Comparing two or more groups or treatment conditions to measure their effects.
Longitudinal Experiments: Measuring changes in the dependent variable over time by conducting multiple experiments at different points in time.
Cross-sectional Experiments: Comparing different groups or populations that exist at the same time to measure the effects of interventions or treatments.
Panel Experiments: Longitudinal experiments that involve the same participants across multiple sessions.
Factorial Experiments: Examining the effects of multiple independent variables on the dependent variable.
Pilot Experiments: Conducted to test the feasibility and appropriateness of the experimental design before implementing it on a larger scale.
Sequential Experiments: Experiment designs in which different stages of the experiment build upon one another to test multiple hypotheses.
Scaling Experiments: Examining the effects of interventions on different levels of measurement, such as individual attitudes, group opinions, and political behavior.
Computer Simulations: Utilizing computer models to simulate political behavior and test the effects of interventions or treatments.
"The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as 'output variables' or 'response variables.'"
"The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results."
"Experimental design involves not only the selection of suitable independent, dependent, and control variables but planning the delivery of the experiment under statistically optimal conditions given the constraints of available resources."
"There are multiple approaches for determining the set of design points (unique combinations of the settings of the independent variables) to be used in the experiment."
"Main concerns in experimental design include the establishment of validity, reliability, and replicability."
"For example, these concerns can be partially addressed by carefully choosing the independent variable, reducing the risk of measurement error, and ensuring that the documentation of the method is sufficiently detailed."
"Related concerns include achieving appropriate levels of statistical power and sensitivity."
"Correctly designed experiments advance knowledge in the natural and social sciences and engineering, with design of experiments methodology recognized as a key tool in the successful implementation of a Quality by Design (QbD) framework."
"Other applications include marketing and policy making."
"The study of the design of experiments is an important topic in metascience."