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# Quantitative methods

TBC
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In this step, I’m going to give an overview of quantitative research methods. This is a big and complex topic. And so I will give just an overview of the different kinds of study designs, and what kinds of questions they answer, and evidence they help to generate. We will discuss this more in the coming week. Quantitative data is numerical in nature. This means it provides information like counts, proportions, and rates. One example of quantitative data is the proportion of people in a population who have a disability, which is also called the prevalence of disability.
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Quantitative data can also be provided to think about whether girls or boys with disabilities are more likely to be out of school, which interventions work best improved school grades of children with disabilities. Quantitative data can be generated through different types of studies. As an example, we may want the study to estimate the proportion of people in the Maldives who have disabilities. Remember, this is called the prevalence of disability. Prevalence is usually measured through surveys. In this, sample of the population is selected and disability is assessed so that we can calculate the percentage of the sample who has a disability, and make inferences to the whole population. This will be discussed further in the coming weeks.
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We may also want to ask other kinds of questions, like what are the differences and characteristics of people with and without disabilities in the Maldives? Survey data can also be used to quantitatively compare different groups and answer this question. For instance, in the Maldives, we compared people with disabilities to those without disabilities and found that people with disabilities were generally older and lived in poorer households. But there is often a limit to how much information we can collect in surveys if we are collecting all the information from all the participants.
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We can use case control studies, where we focus on collecting more in-depth information on people with the condition and a sample of people without the condition. These are called cases and controls. And in our example will be people with disabilities and people without disabilities, with the controls often selected to be the same age and sex and from the same communities as the cases. We can interview people, both cases and controls, in more detail using standardised questionnaires in a case control study. And that allows us to compare people with and without disabilities for a range of characteristics like inclusion in school, level of poverty, and health needs.
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Surveys and case control studies are cross-sectional, which means that we collect data on the condition– in this case, disability– and the outcomes, like education and health, at the same time. Another type of study that I will mention briefly are cohort studies. Here, people are categorised by whether or not they have a condition– in this case, disability– and then are followed forward in time to compare the frequency of different events between the groups. For instance, we did a study in Malawi where we measured disability in a group of people and then compared the mortality rate over the following years between people with and without disabilities. Surveys, case control studies, and cohort studies are all types of observational studies.
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This means that the researcher collects data, but does not intervene, for instance, by giving people different types of treatments. These types of studies are helpful to consider the living conditions of people with disabilities, which helps us to work out what the needs are and where we should direct programmes programmes. No one type of observational study is better than another. And they all have their pros and cons. For instance, cohort studies allow us to be sure that the disability occurred before the outcome. Whereas in other designs, the disability and outcomes are measured at the same time. But cohort studies require a follow-up and so take a long time. And this often costs more money.
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A different type of study design is needed for some questions that we want to answer. For instance, we recently did a study to consider does social protection improve the lives of people with disabilities in the Maldives? This type of question is best answered through an intervention study, where they investigate and measures the impact of an intervention rather than compares groups of people with and without a condition. One type of intervention study is a randomised control trial, where the investigator decides at random whether a person receives an intervention or not. These trials allow us to investigate where the outcomes are better in the group who got the intervention or the group who did not.
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There are important ethical and practical questions to consider when planning an intervention study, whether it is fair to withhold an intervention from one group. For instance, an intervention study would allow us to investigate whether facility or home based care is better for children with disabilities. First, we want to decide which groups of children were eligible. We would also need to define what we mean by better. Is this that the children had better functional outcomes? Or the parents prefer the treatment? Or in the long term the children are more likely to live independently? Sometimes intervention studies also compare the costs as well as the effectiveness of different kinds of interventions. And this allows us to calculate a measure called cost effectiveness.
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Finally, it is rare that only one study is undertaken on a particular subject. A systematic review is used to collect all the similar data together and see what the overall picture shows us. For instance, at the International Centre for Evidence in Disability, we undertook a systematic review of the relationship between poverty and disability in low middle income countries, and found that the studies consistently found a strong association regardless of how we measured disability or poverty.
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In summary, you should now understand that quantitative data refers to numerical information. Quantitative data can be used to answer questions about the frequency, the causes, and the impacts of conditions. There are a number of different quantitative study designs, and each have their pros and cons.

In this step, you will hear from lead educator, Professor Hannah Kuper, about quantitative methods in disability research. In contrast to qualitative methods, which you learnt about in the last step, quantitative methods are used to gather numeric data.

In this video, Professor Kuper describes the types of data collection methods that can be used in quantitative research. This includes cross sectional studies, case control studies, and randomised controlled trials. Later in the course, you will hear from Dr Morgon Banks about how this type of data can be analysed. A summary of the types of research methods that can be used in disability research (both qualitative and quantitative) is provided in Step 1.11.

We would love to hear your thoughts on this video. How do quantitative and qualitative research methods differ?