Cross-sectional Study
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Cross-sectional Study
In medical research, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, ''at a specific point in time''—that is, cross-sectional data. In economics, cross-sectional studies typically involve the use of cross-sectional regression, in order to sort out the existence and magnitude of causal effects of one independent variable upon a dependent variable of interest at a given point in time. They differ from time series analysis, in which the behavior of one or more economic aggregates is traced through time. In medical research, cross-sectional studies differ from case-control studies in that they aim to provide data on the entire population under study, whereas case-control studies typically include only individuals who have developed a specific condition and compare them with a matched sample, o ...
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Medical Research
Medical research (or biomedical research), also known as experimental medicine, encompasses a wide array of research, extending from "basic research" (also called ''bench science'' or ''bench research''), – involving fundamental scientific principles that may apply to a ''preclinical'' understanding – to clinical research, which involves studies of people who may be subjects in clinical trials. Within this spectrum is applied research, or translational research, conducted to expand knowledge in the field of medicine. Both clinical and preclinical research phases exist in the pharmaceutical industry's drug development pipelines, where the clinical phase is denoted by the term ''clinical trial''. However, only part of the clinical or preclinical research is oriented towards a specific pharmaceutical purpose. The need for fundamental and mechanism-based understanding, diagnostics, medical devices, and non-pharmaceutical therapies means that pharmaceutical research i ...
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Census
A census is the procedure of systematically acquiring, recording and calculating information about the members of a given population. This term is used mostly in connection with national population and housing censuses; other common censuses include censuses of agriculture, traditional culture, business, supplies, and traffic censuses. The United Nations (UN) defines the essential features of population and housing censuses as "individual enumeration, universality within a defined territory, simultaneity and defined periodicity", and recommends that population censuses be taken at least every ten years. UN recommendations also cover census topics to be collected, official definitions, classifications and other useful information to co-ordinate international practices. The UN's Food and Agriculture Organization (FAO), in turn, defines the census of agriculture as "a statistical operation for collecting, processing and disseminating data on the structure of agriculture, covering th ...
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Demographics
Demography () is the statistical study of populations, especially human beings. Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as education, nationality, religion, and ethnicity. Educational institutions usually treat demography as a field of sociology, though there are a number of independent demography departments. These methods have primarily been developed to study human populations, but are extended to a variety of areas where researchers want to know how populations of social actors can change across time through processes of birth, death, and migration. In the context of human biological populations, demographic analysis uses administrative records to develop an independent estimate of the population. Demographic analysis estimates are often considered a reliable standard for judging the accuracy of the census information gathered at any time. In the labor fo ...
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Money Demand
In monetary economics, the demand for money is the desired holding of financial assets in the form of money: that is, cash or bank deposits rather than investments. It can refer to the demand for money narrowly defined as M1 (directly spendable holdings), or for money in the broader sense of M2 or M3. Money in the sense of M1 is dominated as a store of value (even a temporary one) by interest-bearing assets. However, M1 is necessary to carry out transactions; in other words, it provides liquidity. This creates a trade-off between the liquidity advantage of holding money for near-future expenditure and the interest advantage of temporarily holding other assets. The demand for M1 is a result of this trade-off regarding the form in which a person's funds to be spent should be held. In macroeconomics motivations for holding one's wealth in the form of M1 can roughly be divided into the transaction motive and the precautionary motive. The demand for those parts of the broader mone ...
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Serial Correlation
Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations of a random variable as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies. It is often used in signal processing for analyzing functions or series of values, such as time domain signals. Different fields of study define autocorrelation differently, and not all of these definitions are equivalent. In some fields, the term is used interchangeably with autocovariance. Unit root processes, trend-stationary processes, autoregressive processes, and moving average processes are specific forms of processes with autocorrelation. Auto ...
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Correlation
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics it usually refers to the degree to which a pair of variables are ''linearly'' related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve. Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling. However ...
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Ecological Fallacy
An ecological fallacy (also ecological ''inference'' fallacy or population fallacy) is a formal fallacy in the interpretation of statistical data that occurs when inferences about the nature of individuals are deduced from inferences about the group to which those individuals belong. "Ecological fallacy" is a term that is sometimes used to describe the fallacy of division, which is not a statistical fallacy. The four common statistical ecological fallacies are: confusion between ecological correlations and individual correlations, confusion between group average and total average, Simpson's paradox, and confusion between higher average and higher likelihood. Examples Mean and median An example of ecological fallacy is the assumption that a population mean has a simple interpretation when considering likelihoods for an individual. For instance, if the mean score of a group is larger than zero, this does not imply that a random individual of that group is more likely to have ...
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Centers For Disease Control
The Centers for Disease Control and Prevention (CDC) is the national public health agency of the United States. It is a United States federal agency, under the Department of Health and Human Services, and is headquartered in Atlanta, Georgia. The agency's main goal is the protection of public health and safety through the control and prevention of disease, injury, and disability in the US and worldwide. The CDC focuses national attention on developing and applying disease control and prevention. It especially focuses its attention on infectious disease, food borne pathogens, environmental health, occupational safety and health, health promotion, injury prevention and educational activities designed to improve the health of United States citizens. The CDC also conducts research and provides information on non-infectious diseases, such as obesity and diabetes, and is a founding member of the International Association of National Public Health Institutes.
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Census Bureau
The United States Census Bureau (USCB), officially the Bureau of the Census, is a principal agency of the U.S. Federal Statistical System, responsible for producing data about the American people and economy. The Census Bureau is part of the U.S. Department of Commerce and its director is appointed by the President of the United States. The Census Bureau's primary mission is conducting the U.S. census every ten years, which allocates the seats of the U.S. House of Representatives to the states based on their population. The bureau's various censuses and surveys help allocate over $675 billion in federal funds every year and it assists states, local communities, and businesses make informed decisions. The information provided by the census informs decisions on where to build and maintain schools, hospitals, transportation infrastructure, and police and fire departments. In addition to the decennial census, the Census Bureau continually conducts over 130 surveys and programs ...
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Cohort Effect
The term cohort effect is used in social science to describe variations in the characteristics of an area of study (such as the incidence of a characteristic or the age at onset) over time among individuals who are defined by some shared temporal experience or common life experience, such as year of birth, or year of exposure to radiation. Cohort effects are important to epidemiologists searching for patterns in illnesses. Certain illnesses may be socially affected via the anticipation phenomenon, and cohort effects can be an indicator of this sort of phenomenon. Cohort effects are important to resource dependency, and economics theorists when these groups affect structures of influence within their larger organizations. Cohorts in organizations are often defined by entry or birth date, and they retain some common characteristic (size, cohesiveness, competition) that can affect the organization. For example, cohort effects are critical issues in school enrollment. In order to de ...
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Recall Bias
Recall may refer to: * Recall (bugle call), a signal to stop * Recall (information retrieval), a statistical measure * ''ReCALL'' (journal), an academic journal about computer-assisted language learning * Recall (memory) * ''Recall'' (Overwatch), a 2016 animated short * ''The Recall'', a 2017 Canadian-American film * Recall election, a procedure by which voters can remove an elected official * Letter of recall, sent to return an ambassador from a country * Product recall * ''Recalled'' (film), a South Korean mystery thriller film * "Recall", a song by Susumu Hirasawa on the 1995 album ''Sim City'' * Recall, UK term for hook flash See also * Perfect recall (other) * Total recall (other) * * * Remember (other) Remember may refer to: Film and television * ''Remember?'', a 1939 film starring Robert Taylor and Greer Garson * Remember (1926 film), ''Remember'' (1926 film), an American silent drama film * Remember (2015 film), ''Remember'' (2015 film ...
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Confounding Factor
In statistics, a confounder (also confounding variable, confounding factor, extraneous determinant or lurking variable) is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations.Pearl, J., (2009). Simpson's Paradox, Confounding, and Collapsibility In ''Causality: Models, Reasoning and Inference'' (2nd ed.). New York : Cambridge University Press. The existence of confounders is an important quantitative explanation why correlation does not imply causation. Confounds are threats to internal validity. Definition Confounding is defined in terms of the data generating model. Let ''X'' be some independent variable, and ''Y'' some dependent variable. To estimate the effect of ''X'' on ''Y'', the statistician must suppress the effects of extraneous variables that influence both ''X'' and ''Y''. We say that ''X'' and ...
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