and pdfFriday, April 23, 2021 11:53:38 PM3

Longitudinal Research Design Advantages And Disadvantages Pdf

longitudinal research design advantages and disadvantages pdf

File Name: longitudinal research design advantages and disadvantages .zip
Size: 12514Kb
Published: 24.04.2021

What is a Longitudinal Study?: Definition and Explanation

Administrative data is the term used to describe everyday data about individuals collected by government departments and agencies. Examples include exam results, benefit receipt and National Insurance payments. Attrition is the discontinued participation of study participants in a longitudinal study. Attrition can reflect a range of factors, from the study participant not being traceable to them choosing not to take part when contacted. Attrition is problematic both because it can lead to bias in the study findings if the attrition is higher among some groups than others and because it reduces the size of the sample.

Biological samples is the term used for specimens collected from human subjects from which biological information, such as genetic markers, can be extracted for analysis. Common examples include blood, saliva or hair. Body mass index is a measure used to assess if an individual is a healthy weight for their height.

Boosted samples are used to overcome sample bias due to attrition or to supplement the representation of smaller sub-groups within the sample. Inclusion of boosted samples must be accompanied by appropriate survey weights. Computer-assisted personal interviewing CAPI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes. The use of computers take place within the context of a face-to-face interview.

Computer-assisted self-interviewing CASI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes. The use of computers take place within the context of a self-completion questionnaire. A categorical variable is a variable that can take one of a limited number of discrete values.

They can be either nominal — they contain no inherent order of categories e. Computer-assisted telephone interviewing CATI is a technique for collecting data from participants using computers to eliminate common errors such as questionnaire routing and data entry mistakes. The use of computers take place within the context of a telephone interview.

For some study participants the exact time of an event will not be known because either: the study ends or the analysis is carried out before they have had the event, or the participant drops out of the study before experiencing the event. It is therefore, only known that the event has not occurred up to the time that they were last observed in the study.

Census refers to a universal and systematic collection of data from all individuals within a population. In the UK, the government conducts a census every ten years with the next one due in A codebook is a document online or hard-copy that contains all the information about how a dataset has been coded, such that it can be deciphered by a researcher not familiar with the original coding frame.

Coding is the process of converting survey responses into numerical codes to facilitate data analysis. All potential responses as well as possible reasons for non-response for each variable are assigned numerical values according to a coding frame.

Cognitive assessments are exercises used to measure thinking abilities, such as memory, reasoning and language. Cohort studies are concerned with charting the lives of groups of individuals who experience the same life events within a given time period. The best known examples are birth cohort studies, which follow a group of people born in a particular period.

Complete case analysis is the term used to describe a statistical analysis that only includes participants for which we have no missing data on the variables of interest. Participants with any missing data are excluded. Examples would include study respondents answering questions differently or even behaving differently as a result of their participation in the study. Confounding occurs where the relationship between independent and dependent variables is distorted by one or more additional, and sometimes unmeasured, variables.

A confounding variable must be associated with both the independent and dependent variables but must not be an intermediate step in the relationship between the two i. We can say that age is a confounder of that relationship as it is associated with, but not caused by, physical activity and is also associated with coronary health.

A continuous variable is a variable that has an infinite number of uncountable values e. They are also known as quantitative variables or scale variables. Cohort effects relates to changes in an outcome associated with being a member of a specific cohort of people e. In metadata management, coverage refers to the temporal, spatial and topical aspects of the data collection to describe the comprehensiveness of a dataset. For longitudinal studies , this can relate to the topics that are covered across waves, the population to which one can generalise or the geographic extent of the dataset.

Cross-sectional surveys involve interviewing a fresh sample of people each time they are carried out. Some cross-sectional studies are repeated regularly and can include a large number of repeat questions questions asked on each survey round. Within the context of data protection , a data access agreement specifies the terms under which users are provided access to specified datasets. This usually forms part of the application process to the data controller to ensure that researchers adhere to a set of terms regarding data confidentiality , sensitivity and dissemination before accessing the data.

See also: research ethics. Data cleaning is an important preliminary step in the data analysis process and involves preparing a dataset so that it can be correctly analysed. Data harmonisation involves retrospectively adjusting data collected by different surveys to make it possible to compare the data that was collected.

This enables researchers to make comparisons both within and across studies. Repeating the same longitudinal analysis across a number of studies allows researchers to test whether results are consistent across studies, or differ in response to changing social conditions.

Data imputation is a technique for replacing missing data with an alternative estimate. There are a number of different approaches, including mean substitution and model-based multivariate approaches. Data linkage simply means connecting two or more sources of administrative, educational, geographic, health or survey data relating to the same individual for research and statistical purposes. For example, linking housing or income data to exam results data could be used to investigate the impact of socioeconomic factors on educational outcomes.

Data protection refers to the broad suite of rules governing the handling and access of information about people.

Data protection principles include confidentiality of responses, informed consent of participants and security of data access. Data structure refers to the way in which data are organised and formatting in advance of data analysis.

In analysis, the dependent variable is the variable you expect to change in response to different values of your independent or predictor variables. A derived variable is a variable that is calculated from the values of other variables and not asked directly of the participants.

It can involve a mathematical calculation e. Diaries are a data collection instrument that is particularly useful in recording information about time use or other regular activity, such as food intake. They have the benefit of collecting data from participants as and when an activity occurs. As such, they can minimise recall bias and provide a more accurate record of activities than a retrospective interview.

Dissemination is the process of sharing information — particularly research findings — to other researchers, stakeholders, policy makers, and practitioners through various avenues and channels, including online, written publications and events.

Dissemination is a planned process that involves consideration of target audiences in ways that will facilitate research uptake in decision-making processes and practice. Dummy variables , also called indicator variables , are sets of dichotomous two-category variables we create to enable subgroup comparisons when we are analysing a categorical variable with three or more categories. Empirical data refers to data collected through observation or experimentation.

Analysis of empirical data can provide evidence for how a theory or assumption works in practice. In metadata management, fields are the elements of a database which describes the attributes of items of data.

General ability is a term used to describe cognitive ability, and is sometimes used as a proxy for intelligent quotient IQ scores. Growth curve modelling is used to analyse trajectories of longitudinal change over time allowing us to model the way participants change over time, and then to explore what characteristics or circumstances influence these patterns of longitudinal change.

Hazard rate refers to the probability that an event of interest occurs at a given time point, given that it has not occurred before. Health assessments refers to the assessments carried out on research participants in relation to their physical characteristics or function.

These can include measurements of height and weight, blood pressure or lung function. Heterogeneity is a term that refers to differences, most commonly differences in characteristics between study participants or samples. It is the opposite of homogeneity, which is the term used when participants share the same characteristics.

Where there are differences between study designs, this is sometimes referred to as methodological heterogeneity. Both participant or methodological differences can cause divergences between the findings of individual studies and if these are greater than chance alone, we call this statistical heterogeneity. See also: unobserved heterogeneity. Household panel surveys collect information about the whole household at each wave of data collection, to allow individuals to be viewed in the context of their overall household.

To remain representative of the population of households as a whole, studies will typically have rules governing how new entrants to the household are added to the study. As a way of encouraging participants to take part in research, they may be offered an incentive or a reward. These may be monetary or, more commonly, non-monetary vouchers or tokens. Incentives are advertised beforehand and can act as an aid to recruitment; rewards are a token of gratitude to the participants for giving their time.

In analysis, an independent variable is any factor that may be associated with an outcome or dependent variable.

For example, the number of hours a student spends on revision may influence their test result. A key principle of research ethics , informed consent refers to the process of providing full details of the research to participants so that they are sufficiently able to choose whether or not to consent to taking part.

To put it another way, it is a measure of how thin or fat the lower and upper ends of a distribution are. It centres on the individual and emphasises the changing social and contextual processes that influence their life over time. Many longitudinal studies focus upon individuals, but some look at whole households or organisations. Metadata refers to data about data, which provides the contextual information that allows you to interpret what data mean. Missing data refers to values that are missing and do not appear in a dataset.

This may be due to item non-response, participant drop-out or attrition or, in longitudinal studies , some data e. Large amounts of missing data can be a problem and lead researchers to make erroneous inferences from their analysis. There are several ways to deal with the issue of missing data, from casewise deletion to complex multiple imputation models. Multi-level modelling refers to statistical techniques used to analyse data that is structured in a hierarchical or nested way.

For example. Multi-level models can account for variability at both the individual level and the group e. Non-response bias is a type of bias introduced when those who participate in a study differ to those who do not in a way that is not random for example, if attrition rates are particularly high among certain sub-groups.

Non-random attrition over time can mean that the sample no longer remains representative of the original population being studied. Two approaches are typically adopted to deal with this type of missing data : weighting survey responses to re-balance the sample , and imputing values for the missing information.

23 Advantages and Disadvantages of Longitudinal Studies

The column covered over 35 common research terms used in the health and social sciences. The complete collection of defined terms is available online or in a guide that can be downloaded from the website. Study design depends greatly on the nature of the research question. In other words, knowing what kind of information the study should collect is a first step in determining how the study will be carried out also known as the methodology. Do we want to compare cholesterol levels among different populations of walkers and non-walkers at the same point in time? Or, do we want to measure cholesterol levels in a single population of daily walkers over an extended period of time? The first approach is typical of a cross-sectional study.

Longitudinal studies are a form of observational research that is used to collect data. When this type of study is performed, a set of data is collected from each subject over a defined period. The same subjects are used for the research, which means the study can sometimes last for months, if not years. It is the type of research that is most commonly performed when seeking out information in medical, sociological, or psychological arenas. Here are the top advantages and disadvantages of longitudinal studies to consider when designing a research study. Many research studies focus on short-term data alone. That means long-term data may offer patterns or information that cannot be collected.

What is a longitudinal study?

While we are building a new and improved webshop, please click below to purchase this content via our partner CCC and their Rightfind service. You will need to register with a RightFind account to finalise the purchase. EN English Deutsch.

Learning Hub

Longitudinal Research

Longitudinal studies are a type of research or survey that primarily uses the method of observation, which entails that they do not involve interfering with the subjects in any means. These studies are also unique in a way that they follow a certain timeline that is entirely dependent on the respondents, which means that data collection could take years depending on the exact timetable put in place. Most of the time, they are used by psychologists who are looking to measure or identify the impact therapy can have over time, involving long time frames and vast amounts of data. Now, like any other type of method in conducting research, longitudinal studies also come with certain disadvantages, while they offer obvious advantages. Here are important things to take note when planning to use this methodology:. They are effective in determining variable patterns over time. Because these studies involve the use and collection of data in long periods of time, they can determine patterns efficiently.

Published on May 8, by Lauren Thomas. In a longitudinal study, researchers repeatedly examine the same individuals to detect any changes that might occur over a period of time. Longitudinal studies are a type of correlational research in which researchers observe and collect data on a number of variables without trying to influence those variables.

Longitudinal research refers to the analysis of data collected at multiple points in time. Skip to main content Skip to table of contents. This service is more advanced with JavaScript available. Encyclopedia of Child Behavior and Development Edition. Editors: Sam Goldstein, Jack A.

Administrative data is the term used to describe everyday data about individuals collected by government departments and agencies. Examples include exam results, benefit receipt and National Insurance payments. Attrition is the discontinued participation of study participants in a longitudinal study.

Longitudinal research is a type of correlational research that involves looking at variables over an extended period of time. This type of study can take place over a period of weeks, months, or even years. In some cases, longitudinal studies can last several decades.

3 Comments

  1. Fourpmighsemusc

    25.04.2021 at 23:15
    Reply

    A longitudinal study involves conducting research over a period of time, longitudinal research, but there are also a number of drawbacks that need to be.

  2. Brittany P.

    30.04.2021 at 17:27
    Reply

    and to account for the impact of each individually. Disadvantages. Numerous challenges are implicit in the study design;. particularly by virtue of this occurring over.

  3. Vedette P.

    03.05.2021 at 21:03
    Reply

    Home Consumer Insights Market Research.

Your email address will not be published. Required fields are marked *