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An Introduction to Quantitative Research Peter Harper. Quantitative Research is dominated by two approaches The Experiment and The Survey. The Experimental Method. William Harvey (1578 - 1657).
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Quantitative Research is dominated by two approachesThe Experiment and The Survey
William Harvey (1578 - 1657) Harvey observed that blood moved around the body in a circle, propelled by the heart out through the arteries and back through the veins. Viewed in the broadest terms, the value of the experimental method is demonstrated.
Francesco Redi (1626 -1697) In the 1600s, it was widely believed that living things could spontaneously generate from non-living, dead, or waste materials because people saw such materials "generate" living things such as mould or maggots. In 1688 the Italian naturalist Francesco Rediset out to test the idea that flies were responsible for the maggots by placing decaying meat in two containers: one open to the air, the other sealed. Meat in the open container eventually became infested with maggots.
Francesco Redi (1626 -1697) In another experiment Redi drank Viper venom to show that it was only dangerous if injected directly into the bloodstream
Isaac Newton (1636 -1727) People were using prisms to experiment with colour, and thought that somehow the prism coloured the light. Newton obtained a prism, and set up his so that a spot of sunlight fell onto it. In their experiments, Descartes, Robert Hooke and Edward Boyle had put a screen close to the other side of the prism and seen that the spot of light came out as a mixture of colour. Newton realised that to get a proper spectrum you needed to move the screen a lot further away.
Isaac Newton (1636 -1727) In the study upstairs at Woolsthorpe, he used the 22 feet from the window to the far wall to project a beautiful spectrum. The white light split into different colours and each colour had been bent a different amount by the prism. But to prove that the prism was not colouring the light, Newton did an Experimentum Crucis - his crucial experiment. He put a screen in the way of his spectrum, and this screen had a slit cut in it, and only let the green light go through.
Isaac Newton (1636 -1727) Then he put a second prism in the green light. If it was the prism that was colouring the light, the green should come out a different colour. The pure green light remained green, unaffected by the prism. Newton had proved that white light was made up of colours mixed together, and the prism merely separated them - he was the first person to understand the rainbow.
Are there methodological differences between the “experiments” undertaken by Harvey and Redi?
Inductive Reasoning Harvey’s experiment illustrates an inductive approach to scientific method. Inductive reasoning is based on meticulous observation, e.g., we can observe that metal expands when it is heated.
Deductive Reasoning Redi’s experiment illustrates a deductiveapproach to scientific method. Deductive reasoning is based on prediction, e.g., we can predict that if we don’t leave periodic gaps in railway tracks they will buckle.
Hypotheses • Central to deductive reasoning is the hypothesis. • HYPOTHESIS: a suggested explanation for a groups of facts or phenomena either accepted as a basis of further verification or accepted as likely to be true.(Collins English Dictionary 2000) • Using this definition the hypothesis can be seen as either: • the purpose of an experiment (testing the hypothesis), e.g., Francesco Redi set out to test the hypothesis that life could spontaneously occur; or, • the product of an experiment (generating the hypothesis), e.g., William Harvey
Variables may or may not cause a change in OutcomeThe dependent variable. InterventionThe independent variable The dependant variable may be influenced by one or more extraneous (confounding) variables. The independent variable and any associated measurements must be reliable and valid. In order to be sure that any change in the dependant variable is the direct result of the independent variable the extraneous variables have to be identified and adequately controlled.
Types of Quantitative Design A Randomised Controlled Trial (RCT) A randomised controlled study is one in which: There are two groups, one intervention group and one control group. The intervention group receives the treatment under investigation, and the control group receives either no treatment or some standard default treatment. Patients are randomly assigned to all groups.
Types of Quantitative Design A Quasi Experiment “A quasi-experimental design is one that looks a bit like an experimental design but lacks the key ingredient -- random assignment. My mentor, Don Campbell, often referred to them as "queasy" experiments because they give the experimental purists a queasy feeling. With respect to internal validity, they often appear to be inferior to randomized experiments. But there is something compelling about these designs; taken as a group, they are easily more frequently implemented than their randomized cousins.” Trochim WM. The Research Methods Knowledge Base, 2nd Edition. Available at: http://trochim.human.cornell.edu/kb/index.htm (version current as of August 16, 2004).
Types of Quantitative Design A Case Control Study Case control studies are studies in which people who are already in a certain condition are compared with people who are not.
Types of Quantitative Design A Cohort Study (Longitudinal) A Cohort Study is a study in which people who presently are in a certain condition and/or who receive a particular intervention are followed over time and compared with another group who are not affected by the condition under investigation.
Types of Quantitative Design A Typical Pyramid of Evidence Source = http://servers.medlib.hscbklyn.edu/ebm/2toc.htm
Systematic Review A systematic review is a comprehensive review of a topic in which all of the primary studies of the highest level of evidence have been systematically identified, appraised and then summarised according to an explicit and reproducible methodology. A systematic review may or may not include a meta-analysis.
A Meta-Analysis A meta-analysis is a review in which the results of all of the included studies are similar enough statistically that the results are combined and analyzed as if it was one study. In general a good systematic review or meta-analysis will be a better guide to practice than an individual article.
Survey Method The most common way of collecting survey data is via a questionnaire. Questionnaires can include both open and closed questions.
Survey Method Questionnaires can be completed on paper (eg. post), electronically (eg. internet) or verbally (eg. by telephone) Questionnaires are usually analysed statistically. Answers to open questions are quantified.
People Population = the total number of people or things available Groups of what? Things The whole population Where do we get these groups from? A sample taken from the population Sampling for Experiments
Population = the total number of people available Group of what? People The whole population Where do we get these groups from? A sample taken from the population Sampling for Surveys
Population and Sampling Total or Theoretical Population Target Population Sample Probability Sampling(Random) Non-Probability Sampling(Non- Random)
Probability Sampling Suitable for homogenous populations each unit should have an equal chance of being chosen. Simple Random Suitable for populations which vary greatly in terms of age, gender, education, experience, illness condition. Stratified Random Units are chosen from the sample frame list at predetermined chosen intervals starting from a randomly chosen point. Systematic Random Suitable for populations which are arranged in clusters e.g.. Hospitals. Clusters are sampled first followed by units within clusters e.g.. Wards. Cluster Random
The size of the sample reflects the population diversity and the study variables The sample is randomly selected and if grouped, randomly allocated The sample is representative of the population Population and Sampling What are the characteristics of an ideal sample for quantitative research?
Statistical Analysis There are two main types of statistics DESCRIPTIVE and INFERENTIAL Experiments are usually analysed using inferential statistics in which statistical significance is inferred. i.e., that the difference observed between two or more variables did not happen by chance alone Surveys are often analysed using both descriptive and inferential statistics
adequate identification and control of extraneous variables Survey & Experiment Experiment Experiment a randomised, representative sample of an adequate size reliable and valid interventions and associated measurements Generalisation The ultimate purpose of quantitative research is to be able to generalise the outcome/s to the population from which the sample was drawn. In order to be able to generalise the outcomes the research must have:
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