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medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R.

Ahlin Č, Stupica D, Strle F, Lusa L - PLoS ONE (2015)

Bottom Line: The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited.The summary tools produce publication-ready tables and graphs.The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer.

View Article: PubMed Central - PubMed

Affiliation: PhD Candidate of Statistics Programme, University of Ljubljana, Ljubljana, Slovenia.

ABSTRACT
In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

No MeSH data available.


Related in: MedlinePlus

Summary tab output for binary variables.The table displays the descriptive statistics for the presence of each symptom; the plot shows the observed proportions of patients that report the presence of the symptom, along with their 95% confidence intervals.
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pone.0121760.g003: Summary tab output for binary variables.The table displays the descriptive statistics for the presence of each symptom; the plot shows the observed proportions of patients that report the presence of the symptom, along with their 95% confidence intervals.

Mentions: The summary tabs report the main characteristics of the data. The basic summary statistics for the uploaded data are displayed in the Data overview tab (number of measurements, number of unique subjects, etc.) (S1 Fig); the main descriptive statistics for the outcome variables, summarized at each evaluation occasion, are displayed in the Summary tab (Fig 3, S2 Fig). Numerical variables are summarized using medians (Me) and interquartile range (IQR), while binary variables are summarized with frequencies and proportions; the number of missing values for each variable is always explicitly stated. The tables also report the 95% confidence intervals (CI) for medians (based on percentile bootstrap with 2000 iterations) or proportions (based on exact binomial method), which are also graphically displayed.


medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R.

Ahlin Č, Stupica D, Strle F, Lusa L - PLoS ONE (2015)

Summary tab output for binary variables.The table displays the descriptive statistics for the presence of each symptom; the plot shows the observed proportions of patients that report the presence of the symptom, along with their 95% confidence intervals.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383594&req=5

pone.0121760.g003: Summary tab output for binary variables.The table displays the descriptive statistics for the presence of each symptom; the plot shows the observed proportions of patients that report the presence of the symptom, along with their 95% confidence intervals.
Mentions: The summary tabs report the main characteristics of the data. The basic summary statistics for the uploaded data are displayed in the Data overview tab (number of measurements, number of unique subjects, etc.) (S1 Fig); the main descriptive statistics for the outcome variables, summarized at each evaluation occasion, are displayed in the Summary tab (Fig 3, S2 Fig). Numerical variables are summarized using medians (Me) and interquartile range (IQR), while binary variables are summarized with frequencies and proportions; the number of missing values for each variable is always explicitly stated. The tables also report the 95% confidence intervals (CI) for medians (based on percentile bootstrap with 2000 iterations) or proportions (based on exact binomial method), which are also graphically displayed.

Bottom Line: The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited.The summary tools produce publication-ready tables and graphs.The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer.

View Article: PubMed Central - PubMed

Affiliation: PhD Candidate of Statistics Programme, University of Ljubljana, Ljubljana, Slovenia.

ABSTRACT
In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

No MeSH data available.


Related in: MedlinePlus