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Definitions

These definitions are used in our courses.

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z

A,

• Action research
  'Small-scale interventions in the functioning of the real world and a close examination of the effects of such interventions' — Halsey (1972).
• Aim
  An aim is a description of intention or broad purpose of research.
• Alternative hypothesis (H₁)
  A prediction that there is a difference between the groups of data being compared. The alternative hypothesis is often the working hypothesis, or research question, in a study.
• Association
  The tendency for two things to occur together.

B

• Bias
  A tendency to misrepresent. The term bias is used in statistics to refer to how far the average statistic lies from the parameter it is estimating, that is, the error that arises when estimating a quantity. Errors from chance will cancel each other out in the long run, those from bias will not.
• Binomial distribution
  Binomial distributions model (some) discrete random variables. When a coin is flipped, the outcome is either a head or a tail ie there are two mutually exclusive possible outcomes. For convenience, one of the outcomes can be termed 'success' and the other outcome termed 'failure'. If a coin is flipped N times, then the binomial distribution can be used to determine the probability of obtaining exactly r successes in the N outcomes. The formula that is used assumes that the events: fall into only two categories (ie are dichotomous); are mutually exclusive; are independent and are randomly selected.
• Blinding
  A lack of awareness of a subject's treatment group. Double-blinding is blinding of assessor as well as subject.

C

• Care organisation
  The organisation(s) that are responsible for providing care to patients (and/or users) and carers who are participating in the research study in question.
• Case-control study
  A type of study that involves identifying patients who have the outcome of interest (cases) and patients who have not (controls), and looking back to see if they had the exposure of interest.
• Case-series
  A report on a series of patients who have the outcome of interest. No control group is included. Contrast with case-control study.
• Categorical variable
  A variable that can take values that represent distinct categories.
• Causality
  The act of one thing actively causing another.
• Central limit theorem (CLT)
  The central limit theorem demonstrates that in large enough samples, the distribution of a sample mean approximates a normal curve, amazingly, regardless of the shape of the distribution from which it is sampled. The larger the value of the sample size (n) the better the approximation to the normal.
• Clinical effectiveness
  A measure of how well an intervention, pharmaceutical, health technology, etc actually achieves its aim in improving health status.
• Clinical trial
  Any planned therapeutic, diagnostic or preventive study involving people and comparing concurrently one intervention with another or with a placebo or with no intervention to determine their relative safety and efficacy.
• Cohort
  A group.
• Cohort study
  A type of study that involves the identification of two groups (cohorts) of patients, one of which received the exposure of interest, and one of which did not. Both groups are followed forward over time and studied for the outcome of interest.
• Confidence interval
  A confidence interval is an interval used to estimate the likely size of a population parameter. It gives an estimated range of values (calculated from a given set of sample data) that has a specified probability of containing the parameter being estimated. Most commonly used are the 95% and 99% confidence intervals that have .95 and .99 probabilities respectively of containing the parameter. The width of the confidence interval gives some indication about how uncertain we are about the unknown population parameter. Confidence intervals are more informative than the simple results of hypothesis tests (where we decide 'reject the null hypothesis' or 'don't reject the null hypothesis') because they provide a range of plausible values for the unknown parameter.
• Confidence interval for a mean
  A confidence interval for a mean specifies a range of values within which the unknown population parameter (in this case, the mean) might lie. The width of the confidence interval provides some indication about how uncertain we are about the unknown population parameter, in this case the mean. We calculate these intervals for different confidence levels, depending on how precise we want to be. We interpret a 95% confidence interval as 'we are 95% confident that the interval contains the true population mean'.
• Confounding
  A measured effect attributed to a variable that is actually due to an unmeasured co-variable.
• Content analysis
  A method of analysis used in qualitative research in which text (notes) are systematically examined by identifying and grouping themes and coding, classifying and developing categories.
• Continuous variable
  A variable that can take any value that represents a measurement.
• Consequences
  The results (measured in some way) of employing a health-care intervention (or pharmaceutical, etc).
• Cost-benefit analysis (CBA)
  A type of economic evaluation in which both the costs and consequences of different interventions are expressed in monetary units.
• Cost-consequences analysis
  This term can be used for a type of cost-effectiveness analysis in which cost implications are presented against a range of different output measures. The decision-maker then decides the relative importance of these.
• Cost-effectiveness analysis (CEA)
  A form of economic evaluation in which consequences of different interventions might vary but can be measured in identical 'natural' health-related units (eg lives saved, cases detected); relative inputs are then costed. Competing interventions are compared in terms of cost per unit of consequence.
• Cost-effectiveness ratio
  The total cost of a programme divided by the effectiveness measure (eg cost per life-year gained) used in cost-effectiveness analysis to select among programmes.
• Cost-minimisation analysis (CMA)
  A form of economic evaluation in which consequences of different interventions are the same and in which only the costs are taken into consideration. The aim is to decide the cheapest way of achieving the same result.
• Cost-utility analysis (CUA)
  A form of economic evaluation in which interventions that produce different consequences in terms of both quantity and quality of life are expressed as utilities (eg QALYs). Different interventions are compared in terms of cost per utility.
• Costs
  The resource implications of undertaking an activity. What is actually measured in the costs will depend upon the type of activity, and also from which perspective the analysis is being taken.
• Critical appraisal
  The fair assessment of research literature, judging the validity of results and conclusions, the contribution to scientific knowledge and the populations to which the conclusions can be applied. A basic tool to aid evidence-based health care.
• Crossover study design
  The administration of two or more experimental therapies in sequence in a specified or random order to the same group of patients.
• Cross-sectional
  A 'snapshot' eg the UK census.
• Cross-sectional study
  A type of study that involves the observation of a defined population at a single point in time or time interval. Exposure and outcome are determined simultaneously (a 'snapshot').

D

• Decision analysis
  An explicit, quantitative approach for prescribing decisions under conditions of uncertainty.
• Degree of freedom (DF)
  A mathematical concept that indicates the number of observations or values in a distribution that are independent of each other or are free to vary. They are used with various measures such as t-tests to refine the results of treatments of probability or chance in determining statistical significance. For example, if you have a distribution of three numbers that could vary but the sum of those numbers has to equal 100, then although you could select three numbers, in reality you only have to select two because the third number is determined by the first two numbers selected. In this case, there are two independent values, or two degrees of freedom.
• Delphi technique
  This technique is essentially a survey method whereby individual members of a panel are asked for written information, which is then fed back to the panel as a whole for further comment with the intention of reaching a consensus.
• Descriptive studies
  These studies describe the state of nature at a point in time.
  
• Diagnosis Related Groups (DRGs)
  The Diagnosis Related Group system classifies patients into groups based on the principal diagnosis, type of surgical procedure, presence or absence of significant co-morbidities or complications, and other relevant criteria. Diagnosis Related Groups are intended to categorise patients into groups that are clinically meaningful and homogeneous with respect to resource use.
• Direct costs
  These are the costs that occur as a result of organising and running the intervention or programme that is being evaluated.
• Disclosure
  The conscientious effort to ensure that participants are given full information pertaining to a research study.
• Discounting
  This is a technique that allows the calculation of present values of inputs and benefits that accrue in the future.
• Dispersion
  The data values in a sample are not all the same: this variation between values is called dispersion. When the dispersion is large, the values are widely scattered; when it is small they are tightly clustered. There are several measures of dispersion eg the standard deviation.
• Distribution
  Measurements on any variable, even the same variable on the same subject will vary. The pattern of variation of a variable is called its distribution, which can be described both mathematically and graphically. In essence, the distribution records all possible numerical values of a variable and how often each value occurs (its frequency). The most well known example of a distribution is the bell-shaped curve.

E

• Economic evaluation
  The process used to relate the cost implications of an intervention (or pharmaceutical product, etc) to its consequences. It covers a number of methods, which vary mainly in the ways the effectiveness of an intervention is measured.
• Effectiveness
  The benefit of an intervention when deployed in the field.
• Efficacy
  The benefit of an intervention under ideal conditions.
• Electronic database
  Information, usually consisting of linked data fields, that can be accessed through an electronic medium (eg via a personal computer that has access to this data). Most electronic databases have a search facility, which allows the reader to look for individual topic components within large sets of indexed data.
• Employing organisation(s)
  The organisation(s) that employ the principal investigator and/or other researchers taking part in the study. The organisation employing the principal investigator will normally hold the contract(s) with the funder(s) of the study. Organisations holding contracts with funders are responsible for the management of the funds provided.
• Estimate
  An estimate is an indication of the value of an unknown quantity based on observed data.
• Estimation
  Estimation is the process by which sample data are used to indicate the value of an unknown quantity in a population. Results of estimation can be expressed as a single value, known as a point estimate; or a range of values, known as a confidence interval.
• Ethics
  A generic term for various ways of understanding and examining the moral conduct of human behaviour and actions. Some approaches are normative (ie they set standards of right of good action) others are descriptive (ie they report on what people believe and how they act).
• Ethnography
  'The study of people in their natural settings; a descriptive account of social life and culture in a defined social system, based on qualitative methods (eg detailed observations, unstructured interviews, analysis of documents)' - Bowling (1997).
• Experimental research
  A research technique in which variables of interest (such as drug treatment or diet) are deliberately manipulated by the researcher.

F

• Face validity
  This is the extent to which we logically believe that the survey is measuring the proper areas. For example, we would logically measure attitudes towards health with questions about health.
• Focus groups
  A method of collective (or group) interview, which explicitly uses the interaction within the group to generate data.
• Frequency distribution
  A frequency distribution shows the number of observations falling into each of several ranges of values. Frequency distributions are portrayed as frequency tables, histograms or polygons.
• Funder(s)
  Organisation(s) that provide funding for the study through contracts, grants or donations to an authorised member of either the employing and/or care organisation.

G

• 'Grey literature'
  Unpublished or un-indexed reports. These can include conference proceedings, non-indexed journals, internal reports, pharmaceutical industry reports and student dissertations and theses.

H

• Hawthorne effect
  The impact of the researcher on the research subjects or setting, notably in changing their behaviour.
• Healthcare Resource Groups
  A data analysis tool for reflecting at aggregate level the interventions that are undertaken and the resources that are required in providing healthcare activities. These groups provide a standard and comparable description of healthcare provision, which is useful for a range of NHS purposes.
• Health services research
  Investigation of the health needs of the community and the effectiveness and efficiency of the provision of services to meet those needs in order to provide information relevant to the planning, management and development of services'.
• Hypothesis
  A hypothesis is a statement of the expected relationship between or among the things being studied.
• Hypothesis testing
  Hypothesis testing is one of the two main branches of inference. Setting up and testing hypotheses is an essential part of statistical inference. In order to formulate such a test, usually some theory has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. For each problem considered the question of interest is simplified into two competing claims/hypotheses between which we have a choice: the null hypothesis (denoted H₀) against the alternative hypothesis (denoted H₁). Special consideration is given to the null hypothesis.

I

• Incremental costs
  These are the additional costs that one programme or intervention imposes over another. An analysis of the incremental costs (and effects) tells us how much extra we would have to pay for the extra effect.
• In-depth interviews
  A face-to-face conversation conducted to explore issues or topics in detail. Pre-set questions are not used, but a defined topic or issues are explored.
• Indirect costs
  These include any costs that are borne by patients or their families as a result of taking part in a health-care intervention that is being evaluated. These costs are mainly productivity losses.
• Informed consent
  A process in which the risks, benefits, and requirements of a research study are explained to people invited to take part in the study. Before entering the study a participant should sign an informed consent form, which should contain in writing the benefits, risks and basic structure of the study.
• Interview
  A social experience, depending on one person, the interviewer, asking a series of questions of another person or group of people.

J, K,

L

• Likert scale
  This refers to a widely used questionnaire format named for its developer, Rensis Likert. Respondents of questionnaires are asked to choose from several responses in a range such as 'strongly agree', 'agree', 'undecided'. 'disagree', and 'strongly disagree'. Each response receives a number rating from 0-5. The five-point Likert scale is most common.

M

• Marginal costs
  This is the additional cost of producing one extra unit of output (eg treating one extra patient).
• Mean
  The average of a set of values.
• MEDLINE
  The US National Library of Medicine's database that contains more than 11 million references to journal articles in the health sciences.
• Meta-analysis
  An overview in which quantitative methods are used to summarise the results of several studies on a single topic. A meta-analysis is used in an attempt to gain greater objectivity, generalisability and precision by including all the available high quality evidence from randomised controlled trials carried out on a specified topic.

N

• Non-experimental research
  Research in which the researcher does not have control over all the variables in the study, eg the researcher cannot assign subjects to interventions.
• Normal distribution
  Normal distributions are a family of distributions that are characterised by a bell-shaped, symmetric curve, with scores more concentrated in the middle than in the tails. They are defined by two parameters: the mean (m, mu) and the standard deviation (s, sigma). Many kinds of data are approximated well by the normal distribution. Many statistical tests assume a normal distribution. Most of these tests work well even if the distribution is only approximately normal and in many cases as long as it does not deviate greatly from normality. The normal distribution plays a vital role in inference.
• Null hypothesis
  The null hypothesis is used in experimental research.  It asserts arbitrarily that there is no relationship among the variables being studied. Then statistical tests are used to determine if any relationship shown by the research data is due to chance alone or to alternative hypotheses.
• Numerical data
  Data that consist of counts, or measurements that can take any value within a given range (eg age, length of hospital stay, blood pressure).
• NHS research
  National Health Service (NHS) research can be defined as a planned activity to generate new knowledge that is generalisable and can be accessed through the search of published articles and the so called 'grey' literature.

O

• Objectives
  Objectives are specific outcomes that can be measured using agreed criteria.
• Observational
  A non-experimental research technique in which observations are made without any intervention on the part of the researcher.
• Observer bias
  A systematic difference between a true situation and that observed owing to observer variation in perception (ie interpretation).
• One-sample t-test
  A one-sample t-test is a hypothesis test for answering questions about the mean where the data are a random sample of independent observations from an underlying normal distribution. The sample has been drawn from a population of given mean and unknown variance (which therefore has to be estimated from the sample).
• One-sided test
  A one-sided test is a statistical hypothesis test in which the values for which we can reject the null hypothesis, H₀ are located entirely in one tail of the probability distribution. The choice between a one-sided and a two-sided test is determined by the purpose of the investigation or prior reasons for using a one-sided test.
• Overhead costs
  This is an accounting term that refers to resources that cover more than one department, centre or programme in an organisation.

P

• Parameters
  Numerical characteristics of populations ie parameters are values, usually unknown (and which therefore have to be estimated), used to represent certain population characteristics. Within a population, a parameter is a fixed value, which does not vary.
• Participants (formerly known as subjects)
  Patients, users, relatives of the deceased, professional carers or members of the public who agree to take part in a study.
• Phenomenology
  'The philosophical belief that, unlike matter, humans have a consciousness. They interpret and experience the world in terms of meanings and actively construct an individual social reality' - Bowling (1997).
• Pilot study
  A trial study carried out before a research design is finalised in order to assist in defining the research question or to test the feasibility, reliability and validity of the proposed study design.
• Placebo
  An inert substance or intervention designed to appear the same as the experimental substance or intervention, but which has no physiological effect.
• Point estimate
  Results of estimation can be expressed as a single value, known as a point estimate.
• Poisson distribution
  Poisson distributions model (some) discrete random variables. Typically, a Poisson random variable is a count of the number of events that occur in a certain time interval or spatial area. For example, the number of cars passing a fixed point in a five minute interval.
• Population
  The entirety of subjects ie it is any entire collection (eg of people or things) from which we might collect data and that we wish to describe or draw conclusions about.
• Population mean
  The average value across the population of subjects.
• Power
  The chance (given by %) that a pre-determined effect in a population can be detected as statistically significant in a sample.
• PreMEDLINE
  In process bibliographic citations for MEDLINE.
• Primary research
  A unique research study that produces original data.
• Principal Investigator
  The person who is designated to take overall responsibility within the team of researchers for the design, conduct and reporting of the study.
• Probability
  A numeric scale measuring degree of chance from 0 to 1 (0% to 100%).
• Proposal
  An application for funding that contains all the information that is necessary to describe the project plans, staff capabilities and funds requested.
• Prospective
  Going forwards in time.
• PubMed
  The US National Centre for Biotechnology Information (NCBI) and US National Library of Medicine's freely available online database and search facility. It contains more than 11 million references to the many indexed biomedical journal articles that are in MEDLINE, PreMEDLINE and other related databases.
• P-value
  The probability of observing in a sample an effect at least as unlikely as that observed when in fact there is no effect in the population.

Q

• Qualitative research
  Research that focuses on the experiences, interpretations, impressions or motivations of an individual or individuals, and that seeks to describe how people view things and why. It relates to beliefs, attitudes and changing behaviour.
• Quality-adjusted life-year (QALY)
  A single measure of outcome, combining the quantity of health improvement and quality of life, which reflects people's preferences for health status.

• Quantitative research
  Research that focuses on measuring and counting facts and the relationships among variables, and that seeks to describe observations through statistical analysis of data. It includes experimental and non-experimental research and descriptive research (research that attempts to describe the characteristics of a sample or population).

R

• Randomisation
  The allocation to a treatment group that is performed at random.
• Randomised controlled trial (RCT)
  A prospective research trial in which a group of individuals is randomised (ie allocated at random) into one or more experimental groups or study groups and a control group. The control group may receive a placebo or an existing treatment and the treatment group(s) will receive the treatment(s) or intervention(s) under investigation. All the groups are followed up for the variables/outcomes of interest.
• Random sample
  A fraction of the population that is selected at random (ie all individuals have an equal chance of selection).
• Range
  The range of a sample (or a data set) is a measure of the spread or the dispersion of the observations. It is the difference between the largest and the smallest observed value of some quantitative characteristic.
• Recall bias
  Systematic error due to the differences in accuracy or completeness of recall to memory of past events or experiences.
• Reliability
  Consistency of measurement (ie something is reliable if you repeat the intervention with the same subject and get a similar/equal finding).
• Research
  Research is the empirical investigation of the relationships between or among several variables.
• Researchers
  Individual(s) conducting the study.
• Research Interview
  An interview that is specifically intended to transfer information (be it 'facts', opinions, attitudes, or knowledge) from one person, the subject or participant, to another person, the interviewer.
• Research protocol
  A detailed written plan that guides the conduct of a research study or investigation.
• Responsible care professional
  The doctor, nurse or social worker who is formally responsible for the care of the participant while they are taking part in the study.
• Retrospective
  Looking backwards in time.
• Risk or risk factor
  Risk is a term that is used by epidemiologists to quantify the likelihood that something will occur. A risk factor is something, which either increases or decreases an individual's risk of developing a disease. However, it does not mean that, if exposed, an individual will definitely contract a particular disease.

S

• Sample
  A fraction, or subset, of a population. By studying the sample, it is hoped to draw valid conclusions about the larger group, the population.
• Sample mean
  The average value across the subjects in a sample. The sample mean is an estimator available for estimating the population mean.
• Sample size
  The sample size is simply the size of the sample.
• Sample variance
  Sample variance is a measure of the spread of or dispersion within a set of sample data.
• Sampling bias
  The tendency for a sample to misrepresent its population for reasons not due to chance.
• Sampling distribution
  The sampling distribution describes probabilities associated with a statistic when a random sample is drawn from a population.
• Sampling variability
  Sampling variability refers to the different values that a given function of the data takes when it is computed for two or more samples drawn from the same population.
• Secondary research
  Research that uses data that has been derived from a primary research study and may include a systematic review of primary research.
• Selection bias
  A bias in assignment or a confounding variable that arises from study design rather than by chance. These can occur when the study and control groups are chosen so that they differ from each other by one or more factors that might affect the outcome of the study.
• Sensitivity analysis
  This is a technique that re-runs the comparison between inputs and consequences, and varies the assumptions that underlie the estimates. The aim of sensitivity analysis is to test the robustness of the conclusions by varying the items about which there is uncertainty.
• Significance level
  The level, set usually at 5% or 1%, below which the p-value would need to be in order to declare that a population effect exists.
• Sponsor
  The organisation that takes primary responsibility for ensuring that the design of the study meets appropriate standards, and that arrangements are in place to ensure appropriate conduct and reporting. The sponsor is usually, but does not have to be, the main funder.
• Standard deviation
  Standard deviation is a measure of variability (spread) or dispersion of a set of data. The more widely the values are spread out, the larger the standard deviation.
• Standard error
  Standard error is a measure of variability. The standard error of a statistic is the standard deviation of the sampling distribution of that statistic. Standard errors are important because they reflect how much sampling fluctuation a statistic will show. The standard error of a statistic depends on the sample size. In general, the larger the sample size the smaller the standard error.
• Statistic
  A statistic is a quantity that is calculated from a sample of data. It is used to give information about unknown values in the corresponding population. It is possible to take more than one sample from the same population and the value of a statistic will in general vary from sample to sample.
• Statistical hypotheses
  Statements about population parameter values.
• Statistical inference
  Statistical inference makes use of information from a sample to draw conclusions (inferences) about the population from which the sample was taken ie it is the act of drawing conclusions about a population from a sample.
• Statistics
  The word 'statistics' is used in several different senses. For example it can be used to refer to a range of techniques and procedures for analysing, interpreting and displaying data. In a second usage, a 'statistic' is defined as a numerical quantity (eg the mean) calculated in a sample ie a numerical summary of sample data. Such statistics are used to estimate parameters.
• Survey
  An investigation in which information is systematically collected, but in which the experimental method is not used.
• Systematic review A review in which evidence about a topic has been systematically identified, appraised and summarised according to predetermined criteria.

T

• Test statistic
  Measures the degree to which a sample is inconsistent with the null hypothesis.
• Triangulation
  The use of three or more different research methods in combination to study the same phenomena, (eg observational studies, in-depth interviews and focus groups). Triangulation is used mainly as a check of validity.
• Two-sample t-test
  A two-sample t-test is a hypothesis test for answering questions about the mean where the data are collected from two random samples of independent observations, each from an underlying normal distribution. The null hypothesis for the two-sample t-test is: H₀ = m₁ = m₂. That is, the two samples have both been drawn from the same population.
• Two-sided test
  A two-sided test is a statistical hypothesis test in which the values for which we can reject the null hypothesis, H₀ are located in both tails of the probability distribution. The choice between a one-sided and a two-sided test is determined by the purpose of the investigation or prior reasons for using a one-sided test.
• Type I error
  In a hypothesis test, a type I error occurs when the null hypothesis is rejected when it is, in fact, true ie H₀ is wrongly rejected. A type I error is usually considered to be more serious, and therefore more important to avoid, than a type II error.
• Type II error
  In a hypothesis test, a type II error occurs when the null hypothesis H₀ is not rejected when it is, in fact, false. A type II error is frequently due to sample sizes being too small.

U, V

• Validity
  True representation or the extent to which the value obtained represents the object of interest in the absence of 'measurement error' (ie something is valid if it measures what it is supposed to measure).

  The internal validity of a study refers to the integrity of the experimental design; the external validity of a study refers to the appropriateness by which its results can be applied to non-study patients or populations.

• Variable
  A variable is an 'object' that is being investigated in a research study and that is considered to be capable of varying. A variable can be (a) dependent ie the effect or response to what the researcher does, or (b) independent ie what the researcher does or controls.

W

• Willingness-to-pay (WTP)
  A technique that relies on the direct eliciting of individual preferences in the views of samples of the general public who are asked how much they would be willing to pay to obtain a benefit or to avoid specified events.

X, Y, Z

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