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**Longitudinal Data Analysis** consists of tools and techniques used to analyze data collected from the same set of variables measures at multiple points of time. The variables that are measured are collected from a wide variety of subjects and studied to gain insights through repeated measurements. Researchers collect longitudinal data in order to draw causal links in the interventions and endpoints. It also helps in controlling the various outcomes by using explanatory variables across the statistical models. During repeated measurement analysis, the subjects are examined under pre-specified conditions and the differences in the results are noted. The results and outcomes are usually measurements and indicators that can vary on several occasions. With the repeated measures taken of the variables, there are various methods suited to the various combinations of these variables. The issue of **omitted variables bias** which is always present with the connections between the outcomes and explanatory variables, is also improved by longitudinal data analysis.

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**SOME IMPORTANT STATISTICS HOMEWORK TOPICS:**

- In longitudinal studies, there is more probability of achieving a similar level of statistical power from a fewer number of subjects.
- The repeated measurements from fewer subjects allow for each subject to be measured providing for independent information than measuring single subjects with single measurements.
- It enables the measurement of within-sample change over time, for measuring the duration of the events and recording the time of the events.
- It also allows the researcher to see the changes of time on the subjects, for example, effects of progressional aging.
- Longitudinal data analysis provides information on individual changes, to understand their growth and changes.

Longitudinal data analysis can be complicated by theoretical and practical issues. The problems can be of missing data or data correlated and collected at irregularly spaced intervals. But modern statistical methods can tackle these issues, yet still have hindrances while using them, while verification of assumptions of correct outcome interpretations. Such confusion can lead to inaccurate analysis. Other challenges are:

**CORRELATED DATA**: Design correlates the measurements in longitudinal studies, ad correlation exists in the repeated measurements on clusters of individuals. If the different sources of correlation in longitudinal data analysis are ignored, there can be severe problems, such as false-positive rates and invalid intervals. Multi-size studies can also lead to the management of a vastly varying number of participants across places. Such unequal sample sizes can lead to power being affected and determined with the smallest sample size.**IRREGULARLY TIMED DATA**: Longitudinal data analysis maintains the practice of regularly repeated visits to the subjects for data collection. Yet issues can occur with participation frequency and study visits due to schedules limitation and midway dropouts.**MISSING DATA**: Issues can arise regarding the missing data since there is no universal correction system regarding the analysis, and therefore wrong and problematic data can bring negative consequences. These consequences can be the decreasing rate of statistical power of the data and increase bias. Missing data can impact the sample sizes and variability.**IT CAN BE EXPENSIVE**: Due to the enormous amounts of time needed to conduct the study, the expense rises and researchers can tend to for small subject groups which make it difficult for the results to be applied to a larger population. Subjects also tend to drop-out of the study, decreasing the sample size and amount of collected data.

Longitudinal data analysis is mostly used for:

- Clinical treatment trials
- Weather
- Stock market
- Medical tests such as pathological tests
- Economic status surveys
- Population conditions
- Study of lifestyles

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**What is Longitudinal Data Analysis Homework Help?****Answer:**Longitudinal data analysis homework help is a service provided by Urgenthomeworkhelp.com where our statistics problem solvers help you to complete your statistics homework, assignments & projects.**What is the process to avail longitudinal data analysis homework help?****Answer:**Just get in touch with us by email ([email protected]), Whatsapp (+1.289.499.9269), or chat with us on our website. Share your assignment details and get a quote from us. Accept our quote by paying for your longitudinal data analysis homework online, on our website. And finally, collect the fully completed homework from your inbox on the agreed delivery date. Its that simple.**What is the benefit to get longitudinal data analysis homework help from UrgentHomeworkHelp.Com?****Answer:**You can get instant and professional longitudinal data analysis homework help at affordable charges, irrespective of how complex it may be.**How long will it take to complete my longitudinal data analysis homework?****Answer:**We can deliver your longitudinal data analysis homework exactly when you need it, even as early as within 24 hours, if required. We will only accept an order if we can deliver it on time.**What other services do you offer?****Answer:**We help with all college & university homework, assignments, essays, dissertations and research-papers. We also help with computer programming assignments. Visit our services page for more information.**Can I pay someone to do my longitudinal data analysis homework?****Answer:**Yes, Our statistics problem solvers provide excellent solutions to help you complete your longitudinal data analysis homework.**Do you provide free longitudinal data analysis homework help?****Answer:**No. Our services are not free, but we try our best to keep our charges low by working directly with some of the best statisticians worldwide.**What is the best website that provides longitudinal data analysis homework help?****Answer:**Urgenthomeworkhelp.com is the best website that provides professional longitudinal data analysis homework help at affordable charges, and we are open 24x7.

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