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Research essentials Understanding the key features of quantitative research and statistical tests QUANTITATIVE RESEARCH is a deductive approach to test theories and hypotheses. These approaches can be descriptive, correlational, quasi-experimental and experimental. Designs to answer different questions using cystic fibrosis (CF) as an example are in the panel below. ■ Descriptive research Explores and describes phenomena without any manipulation. Data are collected through observation, interviews and questionnaires. The data are numerical. ■ Correlational research Explores relationships/ associations between given variables; the extent of an association is known as a correlation coefficient. A positive correlation describes findings when both are variable, while it is negative when one variable increases and the other decreases. The value 1 represents a perfect positive correlation, 0 no correlation and -1 a perfect negative correlation. Tools used to collect data include validated questionnaire or scales.
■ Quasi-experimental research This examines causal relationships between variables. These types of study are considered quasi-experimental because they lack the randomisation seen in experimental studies. ■ Experimental research This is objective, systematic and highly controlled, for example the double-blind randomised controlled trial. It allows causality between independent and dependent variables to be examined under controlled conditions. A range of statistical tests might be used. Sample size in quantitative studies are often large because findings are more likely to be generalised to the population of interest in large samples. Normally, research protocols for quantitative studies are rigidly adhered to ensure the hypothesis is tested effectively. A range of methods are used to collect data, including questionnaires, but can include measures such as weight, height, body mass
index or elements of lung function (see panel). The data are numerical and analysed using statistical methods to test the hypotheses. Reliability is related to consistency and repeatability, and makes a judgement about whether the test or measurement used, if repeated with the same subjects under the same conditions, would produce the same results. Validity refers to the degree to which the concept is being measured. In quantitative research, validity and reliability are assessed using statistical tests estimating the size of error in samples and calculating the significance of findings – typically, P values or confidence intervals. Jane Chudleigh is lecturer in child and adolescent nursing, King’s College London, and Joanna Smith is senior lecturer in children’s nursing, University of Huddersfield. On behalf of the RCN’s Research in Child Health Community
Linking research questions to quantitative studies designs
Geek speak
Question
Null hypothesis (H0) Assumes there is no statistical relationship between two variables.
Possible statistical approaches
Descriptive: collect data on What is the feasibility of recruitment and retention rates of recruiting and retaining newborn screened infants with study participants. cystic fibrosis (CF) and healthy control infants to a longitudinal, observational study?
Means, medians and percentages.
Is there an association between Correlational: record weekly length of the duration of physical activity physical activity (minutes) and lung function in children with CF. and lung function in children with CF?
Linear regression could be used to demonstrate graphically the association between length of physical activity and lung function. Correlation coefficient could be calculated using Spearman’s rho (non-parametric) and Pearson’s product moment (parametric) tests.
Quasi-experimental: a new exercise Does a new exercise regime have any effect on lung function regime would be implemented for children with CF. Lung function in children with CF? would be measured monthly. This type of study could also include, for comparison, groups of healthy controls or children with CF who are not undertaking the new exercise regime.
The independent t-test (parametric) to compare mean lung function results of both groups to determine statistically significant differences.
Which nutritional supplement is more effective for children with CF diagnosed with moderate malnutrition?
The independent t-test (parametric) to compare body mass index in both sets of children, as well as other measures, such as lung function.
Experimental: children with CF with moderate malnutrition randomised to receive one of two supplements. Neither the researcher nor child/parent would be aware which supplement the child receives (double-blind randomised controlled trial).
12 April 2015 | Volume 27 | Number 3
Parametric tests Statistical tests used with ratio or interval data that are normally distributed and homogenous. Non-parametric tests Statistical tests used with ordinal or nominal data that do not need to be normally distributed or homogenous. P value This estimates the probability of rejecting the HO and is conventionally accepted as 5% or 0.05 (less than 1 in 20 chance of being wrong). For example, if the HO states there is no difference in lung function between children with CF and those without and if, following statistical analysis, the P value is found to be ≤0.05, the HO may be rejected. That is, there is a statistically significant difference between the lung function of children with CF and those without. Confidence intervals (CI) Data gathered during studies normally represent a sample of the whole population and are never representative of the entire population. Therefore, while the mean is a useful measure, CIs can be more useful as they tell us the range within the parameter we are investigating.
iStock
Possible research design
NURSING CHILDREN AND YOUNG PEOPLE
Nursing Children and Young People 2015.27:12-12. Downloaded from journals.rcni.com by National University of Singapore on 11/27/15. For personal use only.
Research essentials Understanding the key features of quantitative research and statistical tests QUANTITATIVE RESEARCH is a deductive approach to test theories and hypotheses. These approaches can be descriptive, correlational, quasi-experimental and experimental. Designs to answer different questions using cystic fibrosis (CF) as an example are in the panel below. ■ Descriptive research Explores and describes phenomena without any manipulation. Data are collected through observation, interviews and questionnaires. The data are numerical. ■ Correlational research Explores relationships/ associations between given variables; the extent of an association is known as a correlation coefficient. A positive correlation describes findings when both are variable, while it is negative when one variable increases and the other decreases. The value 1 represents a perfect positive correlation, 0 no correlation and -1 a perfect negative correlation. Tools used to collect data include validated questionnaire or scales.
■ Quasi-experimental research This examines causal relationships between variables. These types of study are considered quasi-experimental because they lack the randomisation seen in experimental studies. ■ Experimental research This is objective, systematic and highly controlled, for example the double-blind randomised controlled trial. It allows causality between independent and dependent variables to be examined under controlled conditions. A range of statistical tests might be used. Sample size in quantitative studies are often large because findings are more likely to be generalised to the population of interest in large samples. Normally, research protocols for quantitative studies are rigidly adhered to ensure the hypothesis is tested effectively. A range of methods are used to collect data, including questionnaires, but can include measures such as weight, height, body mass
index or elements of lung function (see panel). The data are numerical and analysed using statistical methods to test the hypotheses. Reliability is related to consistency and repeatability, and makes a judgement about whether the test or measurement used, if repeated with the same subjects under the same conditions, would produce the same results. Validity refers to the degree to which the concept is being measured. In quantitative research, validity and reliability are assessed using statistical tests estimating the size of error in samples and calculating the significance of findings – typically, P values or confidence intervals. Jane Chudleigh is lecturer in child and adolescent nursing, King’s College London, and Joanna Smith is senior lecturer in children’s nursing, University of Huddersfield. On behalf of the RCN’s Research in Child Health Community
Linking research questions to quantitative studies designs
Geek speak
Question
Null hypothesis (H0) Assumes there is no statistical relationship between two variables.
Possible statistical approaches
Descriptive: collect data on What is the feasibility of recruitment and retention rates of recruiting and retaining newborn screened infants with study participants. cystic fibrosis (CF) and healthy control infants to a longitudinal, observational study?
Means, medians and percentages.
Is there an association between Correlational: record weekly length of the duration of physical activity physical activity (minutes) and lung function in children with CF. and lung function in children with CF?
Linear regression could be used to demonstrate graphically the association between length of physical activity and lung function. Correlation coefficient could be calculated using Spearman’s rho (non-parametric) and Pearson’s product moment (parametric) tests.
Quasi-experimental: a new exercise Does a new exercise regime have any effect on lung function regime would be implemented for children with CF. Lung function in children with CF? would be measured monthly. This type of study could also include, for comparison, groups of healthy controls or children with CF who are not undertaking the new exercise regime.
The independent t-test (parametric) to compare mean lung function results of both groups to determine statistically significant differences.
Which nutritional supplement is more effective for children with CF diagnosed with moderate malnutrition?
The independent t-test (parametric) to compare body mass index in both sets of children, as well as other measures, such as lung function.
Experimental: children with CF with moderate malnutrition randomised to receive one of two supplements. Neither the researcher nor child/parent would be aware which supplement the child receives (double-blind randomised controlled trial).
12 April 2015 | Volume 27 | Number 3
Parametric tests Statistical tests used with ratio or interval data that are normally distributed and homogenous. Non-parametric tests Statistical tests used with ordinal or nominal data that do not need to be normally distributed or homogenous. P value This estimates the probability of rejecting the HO and is conventionally accepted as 5% or 0.05 (less than 1 in 20 chance of being wrong). For example, if the HO states there is no difference in lung function between children with CF and those without and if, following statistical analysis, the P value is found to be ≤0.05, the HO may be rejected. That is, there is a statistically significant difference between the lung function of children with CF and those without. Confidence intervals (CI) Data gathered during studies normally represent a sample of the whole population and are never representative of the entire population. Therefore, while the mean is a useful measure, CIs can be more useful as they tell us the range within the parameter we are investigating.
iStock
Possible research design
NURSING CHILDREN AND YOUNG PEOPLE
Nursing Children and Young People 2015.27:12-12. Downloaded from journals.rcni.com by National University of Singapore on 11/27/15. For personal use only.
