Quasi-experiment in the context of Design of experiments

The design of experiments (DOE), 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. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.

In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." 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.

In economics, the credibility revolution was the movement towards more rigorous empirical analysis. The movement sought to test economic theory and focused on causative econometric modeling and the use of experimental and quasi experimental methods. These more advanced statistical methods gave economists the ability to make causal claims, as the discipline shifted towards a potential outcome framework.

The revolution began in the 1960s when governments began to ask economists to use their skills in economic modeling, econometrics and research design to collect and analyze government data to improve policy making and enforcement of laws. A good example is research on discrimination carried out by the Equal Employment Opportunity Commission (EEOC). Grounded in legally required data from all US employers with 100 or more employees, economists, led by Phyllis Wallace, showed systematic discrimination in employment by race and sex. Their work led to successful discrimination cases in the utility, pharmaceutical and textile industries. Francine Blau and others continued to use EEOC and other data to more rigorously test for wage differentials and occupational segregation by race and sex.

Building science is the science and technology-driven collection of knowledge to provide better indoor environmental quality (IEQ), energy-efficient built environments, and occupant comfort and satisfaction. Building physics, architectural science, and applied physics are terms used for the knowledge domain that overlaps with building science. In building science, the methods used in natural and hard sciences are widely applied, which may include controlled and quasi-experiments, randomized control, physical measurements, remote sensing, and simulations. On the other hand, methods from social and soft sciences, such as case study, interviews & focus group, observational method, surveys, and experience sampling, are also widely used in building science to understand occupant satisfaction, comfort, and experiences by acquiring qualitative data. One of the recent trends in building science is a combination of the two different methods. For instance, it is widely known that occupants' thermal sensation and comfort may vary depending on their sex, age, emotion, experiences, etc. even in the same indoor environment. Despite the advancement in data extraction and collection technology in building science, objective measurements alone can hardly represent occupants' state of mind such as comfort and preference. Therefore, researchers are trying to measure both physical contexts and understand human responses to figure out complex interrelationships.

Building science traditionally includes the study of indoor thermal environment, indoor acoustic environment, indoor light environment, indoor air quality, durability, moisture damage, and building resource use, including energy and building material use. These areas are studied in terms of physical principles, relationship to building occupant health, comfort, and productivity, and how they can be controlled by the building envelope and electrical and mechanical systems. The National Institute of Building Sciences (NIBS) additionally includes the areas of building information modeling, building commissioning, fire protection engineering, seismic design and resilient design within its scope.