A 

A priori analyses  See planned analyses. 
Absolute risk difference  See risk difference. 
Absolute risk reduction  See risk difference. 
Additive model  A statistical model in which the combined effect of several factors is the sum of the effects produced by each of the factors in the absence of the others. For example, if one factor increases risk by a% and a second factor by b%, the additive combined effect of the two factors is (a + b)%. See also multiplicative model. 
Adjusted analysis  An analysis that controls (adjusts) for baseline imbalances in important patient characteristics. See also confounder, regression analysis. 
Adverse event  An adverse outcome that occurs during or after the use of a drug or other intervention but is not necessarily caused by it. 
Adverse effect  An adverse event for which the causal relation between the drug/intervention and the event is at least a reasonable possibility. The term ‘adverse effect’ applies to all interventions, while ‘adverse drug reaction’ (ADR) is used only with drugs. In the case of drugs an adverse effect tends to be seen from the point of view of the drug and an adverse reaction is seen from the point of view of the patient. 
Adverse reaction  See adverse effect 
Aggregate data  Data summarised by groups, for example summary outcome data for treatment and control groups in a controlled trial. 
Allocation concealment  See concealment of allocation. 
Alpha  See Type I error. 
Applicability  See external validity. 
Arithmetic mean  See mean. 
Arm  [In a controlled trial.] Refers to a group of participants allocated a particular treatment. In arandomised controlled trial, allocation to different arms is determined by the randomisation procedure. Many controlled trials have two arms, a group of participants assigned to anexperimental intervention (sometimes called the treatment arm) and a group of participants assigned to a control (the control arm). Trials may have more than two arms, with more than one experimental arm and/or more than one control arm. 
Ascertainment bias  See detection bias. 
Association  A relationship between two characteristics, such that as one changes, the other changes in a predictable way. For example, statistics demonstrate that there is an association between smoking and lung cancer. In a positive association, one quantity increases as the other one increases (as with smoking and lung cancer). In a negative association, an increase in one quantity corresponds to a decrease in the other. Association does not necessarily imply a causal effect. (Also called correlation.) 
Attrition  The loss of participants during the course of a study. (Also called loss to follow up.) Participants that are lost during the study are often call dropouts. 
Attrition bias  Systematic differences between comparison groups in withdrawals or exclusions of participantsfrom the results of a study. For example, participants may drop out of a study because of side effects of an intervention, and excluding these participants from the analysis could result in an overestimate of the effectiveness of the intervention, especially when the proportion dropping out varies by treatment group. 
B 

Baseline characteristics  Values of demographic, clinical and other variables collected for each participant at the beginning of a trial, before the intervention is administered. 
Bayes’ theorem  A probability theorem used to update the probability of an event in the light of a piece of new evidence. A common application is in diagnosis, where the prior probability of disease, obtained from population data, is updated to a posterior probability in the light of a positive or negative result from a diagnostic test. 
Bayesian statistics  An approach to statistics based on application of Bayes’ theorem that can be used in single studies or metaanalysis. A Bayesian analysis uses Bayes’ theorem to transform a priordistribution for an unknown quantity (e.g. an odds ratio) into a posterior distribution for the same quantity, in light of the results of a study or studies. The prior distribution may be based on external evidence, common sense or subjective opinion. Statistical inferences are made by extracting information from the posterior distribution, and may be presented as point estimates, and credible intervals (the Bayesian equivalent of confidence intervals). 
Beta  See Type II error. 
Bias  [In statistics.] A systematic error or deviation in results or inferences from the truth. In studies of the effects of health care, the main types of bias arise from systematic differences in the groups that are compared (selection bias), the care that is provided, exposure to other factors apart from the intervention of interest (performance bias), withdrawals or exclusions of people entered into a study (attrition bias) or how outcomes are assessed (detection bias). Reviews of studies may also be particularly affected by reporting bias, where a biased subset of all the relevant data is available. 
Bias prevention  Aspects of the design or conduct of a study designed to prevent bias. For controlled trials, such aspects include randomisation, blinding and concealment of allocation. 
Binary data  See dichotomous data. 
Binomial distribution  A statistical distribution with known properties describing the number of occurrences of an event in a series of observations. Thus, the number of deaths in the control arm of a controlled trialfollows a binomial distribution. The distribution forms the basis for analyses of dichotomous data. 
Blinding  [In a controlled trial:] The process of preventing those involved in a trial from knowing to which comparison group a particular participant belongs. The risk of bias is minimised when as few people as possible know who is receiving the experimental intervention and who the controlintervention. Participants, caregivers, outcome assessors, and analysts are all candidates for being blinded. Blinding of certain groups is not always possible, for example surgeons in surgical trials. The terms single blind, double blind and triple blind are in common use, but are not used consistently and so are ambiguous unless the specific people who are blinded are listed. (Also called masking.) 
Block randomisation  See random permuted blocks. 
C 

Carry over  [In a crossover trial:] The persistence, into a later period of treatment, of some of the effects of a treatment applied in an earlier period. 
Case series  A study reporting observations on a series of individuals, usually all receiving the sameintervention, with no control group. 
Case study  A study reporting observations on a single individual. (Also called anecdote, case history, orsingle case report.) 
Casecontrol study  A study that compares people with a specific disease or outcome of interest (cases) to people from the same population without that disease or outcome (controls), and which seeks to find associations between the outcome and prior exposure to particular risk factors. This design is particularly useful where the outcome is rare and past exposure can be reliably measured. Casecontrol studies are usually retrospective, but not always. 
Categorical data  Data that are classified into two or more nonoverlapping categories. Race and type of drug (aspirin, paracetamol, etc.) are examples of categorical variables. If there is a natural order to the categories, for example, nonsmokers, exsmokers, light smokers and heavy smokers, the data are known as ordinal data. If there are only two categories, the data are dichotomous data. See also continuous data. 
Causal effect  An association between two characteristics that can be demonstrated to be due to cause and effect, i.e. a change in one causes the change in the other. Causality can be demonstrated by experimental studies such as controlled trials (for example, that an experimental interventioncauses a reduction in mortality). However, causality can often not be determined from anobservational study. 
Censored  [In survival analysis:] A term used in studies where the outcome is the time to a particular event, to describe data from patients where the outcome is unknown. A patient might be known not to have had the event only up to a particular point in time, so ‘survival time’ is censored at this point. 
Chisquared test  A statistical test based on comparison of a test statistic to a chisquared distribution. Used inRevMan analyses to test the statistical significance of the heterogeneity statistic. 
CI  See confidence interval. 
Clinical guideline  A systematically developed statement for practitioners and participants about appropriate health care for specific clinical circumstances. 
Clinical trial  An experiment to compare the effects of two or more healthcare interventions. Clinical trial is an umbrella term for a variety of designs of healthcare trials, including uncontrolled trials,controlled trials, and randomised controlled trials. (Also called intervention study.) 
Clinically significant  A result (e.g. a treatment effect) that is large enough to be of practical importance to patients and healthcare providers. This is not the same thing as statistically significant. Assessing clinical significance takes into account factors such as the size of a treatment effect, the severity of the condition being treated, the side effects of the treatment, and the cost. For instance, if the estimated effect of a treatment for acne was small but statistically significant, but the treatment was very expensive, and caused many of the treated patients to feel nauseous, this would not be a clinically significant result. Showing that a drug lowered the heart rate by an average of 1 beat per minute would also not be clinically significant. 
Cluster randomised trial  A trial in which clusters of individuals (e.g. clinics, families, geographical areas), rather than individuals themselves, are randomised to different arms. In such studies, care should be taken to avoid unit of analysis errors. 
Cohort study  An observational study in which a defined group of people (the cohort) is followed over time. Theoutcomes of people in subsets of this cohort are compared, to examine people who were exposed or not exposed (or exposed at different levels) to a particular intervention or other factor of interest. A prospective cohort study assembles participants and follows them into the future. A retrospective (or historical) cohort study identifies subjects from past records and follows them from the time of those records to the present. Because subjects are not allocated by the investigator to different interventions or other exposures, adjusted analysis is usually required to minimise the influence of other factors (confounders). 
Cointervention  The application of additional diagnostic or therapeutic procedures to people receiving a particular programme of treatment. In a controlled trial, members of either or both the experimental and the control groups might receive cointerventions. 
Comorbidity  The presence of one or more diseases or conditions other than those of primary interest. In a study looking at treatment for one disease or condition, some of the individuals may have other diseases or conditions that could affect their outcomes. (A comorbidity may be a confounder.) 
Concealment of allocation  The process used to ensure that the person deciding to enter a participant into a randomised controlled trial does not know the comparison group into which that individual will be allocated. This is distinct from blinding, and is aimed at preventing selection bias. Some attempts at concealing allocation are more prone to manipulation than others, and the method of allocation concealment is used as an assessment of the quality of a trial. See also bias prevention. (Also called allocation concealment.) 
Confidence interval  A measure of the uncertainty around the main finding of a statistical analysis. Estimates of unknown quantities, such as the odds ratio comparing an experimental intervention with acontrol, are usually presented as a point estimate and a 95% confidence interval. This means that if someone were to keep repeating a study in other samples from the same population, 95% of the confidence intervals from those studies would contain the true value of the unknown quantity. Alternatives to 95%, such as 90% and 99% confidence intervals, are sometimes used. Wider intervals indicate lower precision; narrow intervals, greater precision. (Also called CI.) 
Confidence limits  The upper and lower boundaries of a confidence interval. 
Confounded comparison  A comparison between two treatment groups that will give a biased estimate of the effect of treatment due to the study design. For a comparison to be unconfounded, the two treatment groups must be treated identically apart from the randomised treatment. For instance, to estimate the effect of heparin in acute stroke, a trial of heparin alone versus placebo would provide anunconfounded comparison. However, a trial of heparin alone versus aspirin alone provides a confounded comparison of the effect of heparin. (See also unconfounded comparison.) 
Confounder  A factor that is associated with both an intervention (or exposure) and the outcome of interest. For example, if people in the experimental group of a controlled trial are younger than those in the control group, it will be difficult to decide whether a lower risk of death in one group is due to the intervention or the difference in ages. Age is then said to be a confounder, or a confounding variable. Randomisation is used to minimise imbalances in confounding variables between experimental and control groups. Confounding is a major concern in nonrandomised studies. See also adjusted analyses. 
Consumer (healthcare consumer)  Someone who uses, is affected by, or who is entitled to use a health related service. 
Consumer advocate or representative  Consumer who is actively involved with other consumers and able to represent the perspectives and concerns of that broader group of people. Consumer representatives work in Cochraneentities to ensure that consumers’ views are taken account of when review questions are being decided and results presented. 
Contamination  [In a controlled trial:] The inadvertent application of the intervention being evaluated to people in the control group; or inadvertent failure to apply the intervention to people assigned to theintervention group. Fear of contamination is one motivation for performing a cluster randomised trial. 
Context  The conditions and circumstances that are relevant to the application of an intervention, for example the setting (in hospital, at home, in the air); the time (working day, holiday, nighttime); type of practice (primary, secondary, tertiary care; private practice, insurance practice, charity); whether routine or emergency. 
Contingency table  A table of frequencies or counts. In a twoway contingency table, subcategories of one characteristic are indicated horizontally (in rows) and subcategories of another characteristic are indicated vertically (in columns). Tests of association between the characteristics can be readily applied. The simplest twoway contingency table is the 2×2 table, which is used in clinical trialsto compare dichotomous outcomes, such as death, for an experimental intervention andcontrol group. 
Continuous data  Data with a potentially infinite number of possible values within a given range. Height, weight and blood pressure are examples of continuous variables. See also categorical data. 
Control  1. [In a controlled trial:] A participant in the arm that acts as a comparator for one or more experimental interventions. Controls may receive placebo, no treatment, standard treatment, or an active intervention, such as a standard drug.2. [In a casecontrol study:] A person in the group without the disease or outcomeof interest.3. [In statistics:] To adjust for, or take into account, extraneous influences or observations. 
Control event rate  See risk. 
Control group  1. [In a controlled trial:] The arm that acts as a comparator for one or more experimental interventions. See also control. (Also called comparison group.)2. [In a casecontrol study:] The group without the disease or outcome of interest. (Also calledcomparison group.) 
Control group risk  See risk. 
Control program  [In communicable (infectious) diseases:] Programs aimed at reducing or eliminating the disease. 
Controlled before and after study  A nonrandomised study design where a control population of similar characteristics and performance as the intervention group is identified. Data are collected before and after theintervention in both the control and intervention groups. 
Controlled (clinical) trial (CCT)  See clinical trial. This is an indexing term used in MEDLINE and CENTRAL. Within CENTRAL it refers to trials using quasirandomisation, or trials where double blinding was used butrandomisation was not mentioned. 
Controlled trial  A clinical trial that has a control group. Such trials are not necessarily randomised. 
Convenience sample  A group of individuals being studied because they are conveniently accessible in some way. This could make them particularly unrepresentative, as they are not a random sample of the whole population. A convenience sample, for example, might be all the people at a certain hospital, or attending a particular support group. They could differ in important ways from the people who haven’t been brought together in that way: they could be more or less sick, for example. 
Conventional treatment  Whatever the standard or usual treatment is for a particular condition at that time. 
Correlation  1. See association. (Positive correlation is the same as positive association, and negative correlation is the same as negative association.)2. [In statistics:] Linear association between two variables, measured by a correlation coefficient. A correlation coefficient can range from 1 for perfect negative correlation, to +1 for perfect positive correlation (with perfect meaning that all the points lie on a straight line). A correlation coefficient of 0 means that there is no linear relationship between the variables. 
Costbenefit analysis  An economic analysis that converts effects into the same monetary terms as costs and compares them. 
Costeffectiveness analysis  An economic analysis that views effects in terms of overall health specific to the problem, and describes the costs for some additional health gain (e.g. cost per additional stroke prevented). 
Costutility analysis  An economic analysis that expresses effects as overall health improvement and describes how much it costs for some additional utility gain (e.g. cost per additional qualityadjusted lifeyear). 
Cox model  See proportional hazards model. 
Critical appraisal  The process of assessing and interpreting evidence by systematically considering its validity, results, and relevance. 
Crossover trial  A type of clinical trial comparing two or more interventions in which the participants, upon completion of the course of one treatment, are switched to another. For example, for a comparison of treatments A and B, the participants are randomly allocated to receive them in either the order A, B or the order B, A. Particularly appropriate for study of treatment options for relatively stable health problems. The time during which the firs interventions is taken is known as the first period, with the second intervention being taken during the second period. See also carry over, and period effect. 
Crosssectional study  A study measuring the distribution of some characteristic(s) in a population at a particular point in time. (Also called survey.) 
Cumulative metaanalysis  A metaanalysis in which studies are added one at a time in a specified order (e.g. according to date of publication or quality) and the results are summarised as each new study is added. In a graph of a cumulative metaanalysis, each horizontal line represents the summary of the results as each study is added, rather than the results of a single study. 
F 

Factorial design  A trial design used to assess the individual contribution of treatments given in combination, as well as any interactive effect they may have. Most trials only consider a single factor, where anintervention is compared with one or more alternatives, or a placebo. In a trial using a 2×2 factorial design, participants are allocated to one of four possible combinations. For example in a 2×2 factorial RCT of nicotine replacement and counselling, participants would be allocated to: nicotine replacement alone, counselling alone, both, or neither. In this way it is possible to test the independent effect of each intervention on smoking cessation and the combined effect of (interaction between) the two interventions. This type of study is usually carried out in circumstances where no interaction is likely. 
False negative  A falsely drawn negative conclusion.[In diagnostic tests:] A conclusion that a person does not have the disease or condition being tested, when they actually do.[In clinical trials:] See Type II error. 
False positive  A falsely drawn positive conclusion.[In diagnostic tests:] A conclusion that a person does have the disease or condition being tested, when they actually do not.[In clinical trials:] See Type I error. 
Fixedeffect model  [In metaanalysis:] A model that calculates a pooled effect estimate using the assumption that all observed variation between studies is caused by the play of chance. Studies are assumed to be measuring the same overall effect. An alternative model is the randomeffects model. 
Followup  The observation over a period of time of study/trial participants to measure outcomes under investigation. 
Forest plot  A graphical representation of the individual results of each study included in a metaanalysistogether with the combined metaanalysis result. The plot also allows readers to see theheterogeneity among the results of the studies. The results of individual studies are shown as squares centred on each study’s point estimate. A horizontal line runs through each square to show each study’s confidence interval – usually, but not always, a 95% confidence interval. The overall estimate from the metaanalysis and its confidence interval are shown at the bottom, represented as a diamond. The centre of the diamond represents the pooled point estimate, and its horizontal tips represent the confidence interval. 
Funnel plot  A graphical display of some measure of study precision plotted against effect size that can be used to investigate whether there is a link between study size and treatment effect. One possible cause of an observed association is reporting bias. 
G 

Generalisability (also: applicability, external validity)  See external validity. 
Gold standard  The method, procedure, or measurement that is widely accepted as being the best available, against which new developments should be compared. 
Grey literature  Grey literature is the kind of material that is not published in easily accessible journals or databases. It includes things like conference proceedings that include the abstracts of the research presented at conferences, unpublished theses, and so on. 
H 

Hazard rate  The probability of an event occurring given that it hasn’t occurred up to the current point in time. 
Hazard ratio  A measure of effect produced by a survival analysis. This represents the increased risk with which one group is likely to experience the outcome of interest. For example, if the hazard ratio for death for a treatment is 0.5, then we can say that treated patients are likely to die at half the rate of untreated patients. 
Heterogeneity  1. Used in a general sense to describe the variation in, or diversity of, participants,interventions, and measurement of outcomes across a set of studies, or the variation in internalvalidityof those studies.2. Used specifically, as statistical heterogeneity, to describe the degree of variation in the effect estimatesfrom a set of studies. Also used to indicate the presence of variability among studies beyond the amount expected due solely to the play of chance.See also homogeneous, I2. 
Heterogeneous  Used to describe a set of studies or participants with sizeable heterogeneity. The opposite ofhomogeneous. 
Historical control  A control person or group for whom data were collected earlier than for the group being studied. There is a large risk of bias in studies that use historical controls due to systematic differences between the comparison groups, due to changes over time in risks, prognosis, health care, etc. 
Homogeneous  1. Used in a general sense to mean that the participants, interventions, and measurement ofoutcomesare similar across a set of studies.2. Used specifically to describe the effect estimatesfrom a set of studies where they do not vary more than would be expected by chance.See also homogeneous, heterogeneity. 
Hypothesis  An unproved theory that can be tested through research. To properly test a hypothesis, it should be prespecified and clearly articulated, and the study to test it should be designed appropriately. See also null hypothesis. 
Hypothesis test  A statistical procedure to determine whether to reject a null hypothesis on the basis of the observed data. 
I 

I2  A measure used to quantify heterogeneity. It describes the percentage of the variability in effect estimates that is due to heterogeneity rather than sampling error (chance). A value greater than 50% may be considered to represent substantial heterogeneity. 
Incidence  The number of new occurrences of something in a population over a particular period of time, e.g. the number of cases of a disease in a country over one year. 
Independent  A description of two events, where knowing the outcome or value of one does not inform us about the outcome or value of the other. Formally, two events ‘A and B’ are independent if the probability that A and B occur together is equal to the probability of A occurring multiplied by the probability of B occurring. 
Independent variable  An exposure, risk factor, or other characteristic that is hypothesized to influence the dependent variable. In a clinical trial, the outcome (over which the investigator has no direct control) is the dependent variable, and the treatment arm is the independent variable. In an adjusted analysis, patient characteristics are included as additional independent variables. (Also called explanatory variable.) 
Individual patient data  [In metaanalysis:] The availability of raw data for each study participant in each included study, as opposed to aggregate data (summary data for the comparison groups in each study). Reviews using individual patient data require collaboration of the investigators who conducted the original studies, who must provide the necessary data. 
Intention to treat analysis  A strategy for analysing data from a randomised controlled trial. All participants are included in the arm to which they were allocated, whether or not they received (or completed) theintervention given to that arm. Intentiontotreat analysis prevents bias caused by the loss of participants, which may disrupt the baseline equivalence established by randomisation and which may reflect nonadherence to the protocol. The term is often misused in trial publications when some participants were excluded. 
Interaction  The situation in which the effect of one independent variable on the outcome is affected by the value of a second independent variable. In a trial, a test of interaction examines whether thetreatment effect varies across subgroups of participants. See also factorial trial, subgroup analysis. 
Interim analysis  Analysis comparing intervention groups at any time before the formal completion of a trial, usually before recruitment is complete. Often used with stopping rules so that a trial can be stopped if participants are being put at risk unnecessarily. Timing and frequency of interim analyses should be specified in the protocol. 
Intermediary outcomes  See surrogate endpoints. 
Internal validity  The extent to which the design and conduct of a study are likely to have prevented bias. Variation in quality can explain variation in the results of studies included in a systematic review. More rigorously designed (better quality) trials are more likely to yield results that are closer to the truth. (Also called methodological quality but better thought of as relating to bias prevention.) See also external validity, validity, bias prevention. 
Interrater reliability  The degree of stability exhibited when a measurement is repeated under identical conditions by different raters. Reliability refers to the degree to which the results obtained by a measurement procedure can be replicated. Lack of interrater reliability may arise from divergences between observers or instability of the attribute being measured. See also intrarater reliability. 
Interrupted time series  A research design that collects observations at multiple time points before and after anintervention (interruption). The design attempts to detect whether the intervention has had an effect significantly greater than the underlying trend. 
Intervention  The process of intervening on people, groups, entities or objects in an experimental study. Incontrolled trials, the word is sometimes used to describe the regimens in all comparison groups, including placebo and notreatment arms. See also treatment, experimental intervention and control. 
Intervention group  A group of participants in a study receiving a particular health care intervention. Parallel group trials include at least two intervention groups. 
Intervention study  See Clinical trial. 
Intrarater reliability  The degree of stability exhibited when a measurement is repeated under identical conditions by the same rater. Reliability refers to the degree to which the results obtained by a measurement procedure can be replicated. Lack of intrarater reliability may arise from divergences between instruments of measurement, or instability of the attribute being measured. 
K 

Key words  A string of words attached to an article to be used to index or code the article in a database. See also MeSH 
L 

L’Abbé plot  A scatter plot of the risk in the experimental group against the risk in the control group. Ideally the size of the plotting symbols should be proportional to the size of the trials. Trials in which the experimental treatment had a higher risk than the control will be in the upper left of the plot, between the y axis and the line of equality. If experimental is no better than control then the point will fall on the line of equality, and if the control treatment has a higher risk than the experimental treatment then the point will be in the lower right of the plot, between the x axis and the line of equality. 
Linear scale  A scale that increases in equal steps. In a linear scale on a RevMan forest plot, the distance between 0 and 5 is the same as the distance between 5 and 10, or between 10 and 15. A linear scale may be used when the range of numbers being represented is not large, or to represent differences. See also logarithmic scale. 
Logarithmic scale  A scale in which the logarithm of a value is used instead of the value. In a logarithmic scale on aRevMan forest plot, the distance between 1 and 10 is the same as the distance between 10 and 100, or between 100 and 1000. A logarithmic scale may be used when the range of numbers being represented is large, or to represent ratios. See also linear scale. 
Logistic regression  A form of regression analysis that models an individual’s odds of disease or some other outcome as a function of a risk factor or intervention. It is widely used for dichotomous outcomes, in particular to carry out adjusted analysis. See also metaregression. 
Logodds ratio  The (natural) log of the odds ratio. It is used in statistical calculations and in graphical displays of odds ratios in systematic reviews. 
Loss to follow up  See attrition. 
M 

Masking  See blinding. 
Matching  [In a casecontrol study:] Choosing one or more controls with particular matching attributes for each case. Researchers match cases and controls according to particular variables that are thought to be important, such as age and sex. 
Mean  An average value, calculated by adding all the observations and dividing by the number of observations. (Also called arithmetic mean.) 
Mean difference  [In metaanalysis:] A method used to combine measures on continuous scales (such as weight), where the mean, standard deviation and sample size in each group are known. The weight given to the difference in means from each study (e.g. how much influence each study has on the overall results of the metaanalysis) is determined by the precision of its estimate of effect and, in the statistical software in RevMan and the Cochrane Database of Systematic Reviews, is equal to the inverse of the variance. This method assumes that all of the trials have measured the outcome on the same scale. See also standardised mean difference. (Also called WMD,weighted mean difference.) 
Median  The value of the observation that comes half way when the observations are ranked in order. 
Metaanalysis  The use of statistical techniques in a systematic review to integrate the results of included studies. Sometimes misused as a synonym for systematic reviews, where the review includes a metaanalysis. 
Metaregression  [In metaanalysis:] A technique used to explore the relationship between study characteristics (e.g. concealment of allocation, baseline risk, timing of the intervention) and study results (the magnitude of effect observed in each study) in a systematic review. See also logistic regression. 
Methodological quality  See internal validity, bias prevention. 
Minimisation  A method of allocation used to provide comparison groups that are closely similar for severalvariables. The next participant is assessed with regard to several characteristics, and assigned to the treatment group that has so far had fewer such people assigned to it. It can be done with a component of randomisation, where the chance of allocation to the group with fewer similar participants is less than one. Minimisation is best performed centrally with the aid of a computer program to ensure concealment of allocation. 
Morbidity  Illness or harm. See also comorbidity. 
Mortality  Death. 
Multiarm trial  A trial with more than two arms. 
Multicentre trial  A trial conducted at several geographical sites. Trials are sometimes conducted among several collaborating institutions, rather than at a single institution – particularly when very large numbers of participants are needed. 
Multiple comparisons  The performance of multiple analyses on the same data. Multiple statistical comparisons increase the probability of making a Type I error, i.e. attributing a difference to an intervention when chance is a reasonable explanation. 
Multiplicative model  A statistical model in which the combined effect of several factors is the product of the effects produced by each in the absence of the others. For example, if one factor multiplies risk by a% and a second factor by b%, the combined effect of the two factors is a multiplication by (a x b)%. See also additive model. 
Multivariate analysis  Measuring the impact of more than one variable at a time while analysing a set of data, e.g. looking at the impact of age, sex, and occupation on a particular outcome. Performed usingregression analysis. 
V 

Validity  The degree to which a result (of a measurement or study) is likely to be true and free of bias(systematic errors). Validity has several other meanings, usually accompanied by a qualifying word or phrase; for example, in the context of measurement, expressions such as ‘construct validity’, ‘content validity’ and ‘criterion validity’ are used. See also external validity, internal validity. 
Variable  A factor that differs among and between groups of people. Variables include patient characteristics such as age, sex, and smoking, or measurements such as blood pressure or depression score. There can also be treatment or condition variables, e.g. in a childbirth study, the length of time someone was in labour, and outcome variables. The set of values of a variable in a population or sample is known as a distribution. 
Variance  A measure of the variation shown by a set of observations, equal to the square of the standard deviation. It is defined as the sum of the squares of deviations from the mean, divided by the number of observations minus one. 
W 

Washout period/phase  [In a crossover trial:] The stage after the first treatment is withdrawn, but before the second treatment is started. The washout period aims to allow time for any active effects of the first treatment to wear off before the new one gets started. 
Weighted least squares regression  [In metaanalysis:] A metaregression technique for estimating the parameters of a regression model, wherein each study’s contribution to the sum of products of the measured variables (study characteristics) is weighted by the precision of that study’s estimate of effect. 
Weighted mean difference  See mean difference. 
WMD  See mean difference. 
Z 

Z  [On a forest plot in RevMan:] The value of the test for the overall effect of treatment , from which a pvalue is derived. 
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