Neuroinformatic-
It is known as a research field specifically for the development of neuroscience data knowledge and the support of computational models and analytical tools for integration, sharing, and analysis of experimental data and theory advancement about the nervous system function. It refers to scientific information about vital experimental data, metadata, ontology, analytical tools, and computational models of the nervous system. The general data contains experimental conditions concerning the genomic, structural, molecular, cellular, networks, systems, and behavioural level.Â
Longitudinal study-Â
This research was conducted over an extensive period. It is often used in medical research and sociology, and psychology studies. While using this method, a longitudinal survey pays the tortious insights while having time to get engaged in long research projects. This study is used for surveys to collect either quantitative or qualitative data. Furthermore, creators don’t interfere with survey participants in a longitudinal study. Instead, the survey creator delivers questionnaires to observe changes in participants, attitudes, or behaviours during the same period.
Correlation data analysis-Â Â
Researchers use correlation analysis to figure out the quantitative data collected through research methods like surveys and live interactions. In research, it is a statistical method used to figure out the strength of the linear relationship among two variables and compute the association. It calculates the level of changes in one variable due to the change in one another. A high correlation mentions a strong bond among the variables, while a low correlation is considered a weakly rated variable.Â
Missing data measurement error-Â
Social scientists spend their efforts mitigating measurement error during data collection that is often ignored in data analysis. Scientists routinely figure out the issue of measurement error in data collection. Many statistical methods have been come to reduce measurement error, but a few have been broadly used because of improbable anticipations. We develop an alternative without these challenges.Â
Event history analysis-Â
It is a term generally used to describe various statistical methods designed to explain, describe, or predict the event’s occurrence. Beyond the social sciences, these principles are called survival analysis, which admits that biostatisticians developed them to analyze deaths. Despite their biomedical enactment, these same principles are ideally suitable for studying a broad array of social phenomena like birth, divorces, marriages, job termination, promotion, migrations, and revolutions. Many other names for event history analysis include time failure analysis, transition analysis, hazard analysis, and duration analysis.