Quantitative Research Methods
Glossary of Research Terms and Methodologies |
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QUANTITATIVE RESEARCH METHODS
Research that generates numerical data or data that can be converted into numbers. An example is research using clinical trials. Another example is the Census of England and Wales, which counts people and households. It might involve questions such as 'How many people visit their GP each year?' or 'What proportion of children have had this vaccine?'.
AGGREGATE
A total created from smaller units; the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county.
COHORT STUDY
A group of people sharing a common demographic experience who are observed through time. For example, all the people born in the same year constitute a birth cohort. All the people married in the same year constitute a marriage cohort.
CONFIDENCE INTERVAL
A range of estimated values that is the best guess as to the true population's value. Confidence intervals are usually calculated for the sample mean. In behavioural research, the acceptable level of confidence is usually 95%. Statistically, this means that if 100 random samples were drawn from a population and confidence intervals were calculated for the mean of each of the samples, 95 of the confidence intervals would contain the population's mean. For example, a 95% confidence interval for IQ of 95 to 105, indicates with 95% certainty that the actual average IQ in the population lies between 95 and 105.
CROSS-OVER DESIGN
A crossover design (also called switch over or change over design) is a type of experimental design in which each research subject receives a sequence of experimental treatments over a number of time periods. A major advantage of the crossover design is that each subject serves as his or her own control. They often require a smaller number of participants than more traditional Randomized Control Trial designs.
FIXED EFFECTS REGRESSION TECHNIQUES
Fixed Effects Regression techniques that can be used to eliminate biases associated with the omission of unmeasured characteristics. Biases are eliminated by including an individual-specific intercept term for all cases.
FUNNEL PLOT
A visual way of showing how the results of several studies of the same treatment vary. Usually the effect of treatment in each study is plotted on a graph against the number of people involved. Ideally, the points fall into an inverted funnel shape. If they do not, publication bias or other problems are likely.
HYPOTHESIS TESTING RESEARCH
Statistical tests to determine whether a hypothesis is accepted or rejected. In hypothesis testing, two hypotheses are used: the null hypothesis and the alternative hypothesis. The alternative hypothesis is the hypothesis of interest; it generally states that there is a relationship between two variables. The null hypothesis states the opposite, that there is no relationship between two variables.
MAXIMUM LIKELIHOOD ESTIMATION
Maximum-likelihood estimation (MLE) is one of the most widely used methods for estimating the parameters of a statistical model (for example, means and variances) from sample data. Using the sample data, MLE obtains estimates of the population parameters such that the probability (likelihood) of obtaining the observed data is maximized.
META ANALYSIS AND SYNTHESIS
A statistical technique that combines and analyses data across multiple studies on a topic. In early childhood and education research, a meta-analysis combines a number of studies (usually conducted by a number of different researchers in a variety of contexts) to quantify the effect a given independent or treatment variable (e.g., full-day versus part-day kindergarten and class size) has on a given outcome (e.g., children's academic skills and prevalence of positive and negative classroom behaviour).
NUMBER NEEDED TO TREAT
The average number of patients who need to receive the treatment or other intervention for one of them to get the positive outcome in the time specified. The closer the NNT is to 1, the more effective the treatment.
ODDS RATIO
Compares the odds (probability) of something happening in 1 group with the odds of it happening in another. An odds ratio of 1 shows that the odds of the event happening (for example, a person developing a disease or a treatment working) is the same for both groups. An odds ratio of greater than 1 means that the event is more likely in the first group than the second. An odds ratio of less than 1 means that the event is less likely in the first group than in the second group.
PLACEBO THERAPY
A fake (or dummy) treatment given to patients in the control group of a clinical trial. It is indistinguishable from the actual treatment (which is given to patients in the experimental group). The aim is to determine what effect the experimental treatment has had - over and above any placebo effect caused because someone has had (or thinks they have had) care or attention.
P-VALUE
The probability that the results of a statistical test were due to chance. A p-value greater than .05 is usually interpreted to mean that the results were not statistically significant. Sometimes researchers use a p-value of .01 or a p-value of .10 to indicate whether a result is statistically significant. The lower the p-value the more rigorous the criteria for concluding significance.
QALYS (QUALITY ADJUSTED LIFE YEARS)
A measure of the state of health of a person or group in which the benefits, in terms of length of life, are adjusted to reflect the quality of life. One QALY is equal to 1 year of life in perfect health.
QALYs are calculated by estimating the years of life remaining for a patient following a particular treatment or intervention and weighting each year with a quality-of-life score (on a 0 to 1 scale). It is often measured in terms of the person’s ability to carry out the activities of daily life, and freedom from pain and mental disturbance.
RISK
According to the DCYA’s guidance (2012: 2) ‘one of the main concerns in research ethics is the protection of participants from harm or the limitation of risk of harm. Risk refers to potential harm (physical, psychological or social) that may arise from the research. Research could result in different types of harm, for example, mental distress or the stigmatising of certain social, cultural, racial or religious groups’. Degrees of risk may vary for participants. Applicants must assess and put in adequate protection measures to mitigate against potential harm to research participants.
SAMPLING
The process of selecting a subgroup of a population (i.e. sample) that will be used to represent the entire population.
SAMPLING THEORETICAL
Theoretical sampling can be defined as a process of data collection for generating theory where the analyst jointly collects, codes and analyses his data and decides what data to collect next and where to find them in order to develop his theory as it emerges.
SECONDARY DATA COLLATION AND ANALYSIS
Secondary data analysis is the analysis of data that was collected by someone else
STATISTICAL ANALYSIS
Statistical analysis is the process of collecting, examining, manipulating, summarizing and interpreting quantitative or numerical data for the purpose of identifying patterns, trends, and relationships in the data. It can include the use of descriptive statistics such as percentages, means, variances and correlations and/or the use of inferential statistics such as t-tests, chi-square tests, regression, and analysis of variance (ANOVA).
SURVEY, CROSS-SECTIONAL (also known as CROSS SECTIONAL STUDY)
A 'snapshot' observation of a set of people at 1 time. This type of study contrasts with a longitudinal study, which follows a set of people over a period of time.
SURVEY, LONGITUDINAL
A study of the same group of people at different times. This contrasts with a cross-sectional study, which observes a group of people at a point in time.
SURVEY, QUANTITATIVE
Research that generates numerical data or data that can be converted into numbers. An example is research using clinical trials. Another example is the Census of England and Wales, which counts people and households. It might involve questions such as 'How many people visit their GP each year?' or 'What proportion of children have had this vaccine?'.
SURVIVAL CURVE
Survival curve is a curve that starts at 100% of the study population and shows the percentage of the population still surviving at successive time intervals.
Glossary of Research Terms and Methodologies |
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