Statistical significanceIn statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value of a result, , is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is statistically significant, by the standards of the study, when .
Coronary artery diseaseCoronary artery disease (CAD), also called coronary heart disease (CHD), ischemic heart disease (IHD), myocardial ischemia, or simply heart disease, involves the reduction of blood flow to the heart muscle due to build-up of atherosclerotic plaque in the arteries of the heart. It is the most common of the cardiovascular diseases. Types include stable angina, unstable angina, myocardial infarction, and sudden cardiac death. A common symptom is chest pain or discomfort which may travel into the shoulder, arm, back, neck, or jaw.
AtherosclerosisAtherosclerosis is a pattern of the disease arteriosclerosis in which the wall of the artery develops abnormalities, called lesions. These lesions may lead to narrowing due to the buildup of atheromatous plaque. At onset there are usually no symptoms, but if they develop, symptoms generally begin around middle age. When severe, it can result in coronary artery disease, stroke, peripheral artery disease, or kidney problems, depending on which arteries are affected. The exact cause is not known and is proposed to be multifactorial.
Apolipoprotein BApolipoprotein B (ApoB) is a protein that in humans is encoded by the gene. It is commonly used to detect risk of atherosclerotic cardiovascular disease. Apolipoprotein B is the primary apolipoprotein of chylomicrons, VLDL, Lp(a), IDL, and LDL particles (LDL—commonly known as "bad cholesterol" when in reference to both heart disease and vascular disease in general), which is responsible for carrying fat molecules (lipids), including cholesterol, around the body to all cells within all tissues.
HyperlipidemiaHyperlipidemia is abnormally elevated levels of any or all lipids (fats, cholesterol, or triglycerides) or lipoproteins in the blood. The term hyperlipidemia refers to the laboratory finding itself and is also used as an umbrella term covering any of various acquired or genetic disorders that result in that finding. Hyperlipidemia represents a subset of dyslipidemia and a superset of hypercholesterolemia. Hyperlipidemia is usually chronic and requires ongoing medication to control blood lipid levels.
Sampling (statistics)In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.
Statistical hypothesis testingA statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see .
Repeated measures designRepeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed. Crossover study A popular repeated-measures design is the crossover study. A crossover study is a longitudinal study in which subjects receive a sequence of different treatments (or exposures).
Sampling errorIn statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. It can produced biased results. Since the sample does not include all members of the population, statistics of the sample (often known as estimators), such as means and quartiles, generally differ from the statistics of the entire population (known as parameters). The difference between the sample statistic and population parameter is considered the sampling error.
Stratified samplingIn statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should define a partition of the population.