Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Qualitative Analysis01:10

Qualitative Analysis

1.8K
Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
There are two main approaches to qualitative analysis:...
1.8K
Qualitative Analysis03:46

Qualitative Analysis

28.4K
For solutions containing mixtures of different cations, the identity of each cation can be determined by qualitative analysis. This technique involves a series of selective precipitations with different chemical reagents, each reaction producing a characteristic precipitate for a specific group of cations. Metal ions within a group are further separated by varying the pH, heating the mixture to redissolve a precipitate, or adding other reagents to form complex ions.
For instance, group IV...
28.4K
Quantitative Analysis01:12

Quantitative Analysis

1.8K
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
1.8K
Econometric Views (EViews)01:29

Econometric Views (EViews)

668
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
668
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

17.1K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
17.1K
Interpreting Run Charts01:25

Interpreting Run Charts

4.2K
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
4.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cross-Sectional Time Series Designs: A General Transformation Approach.

Multivariate behavioral research·2016
Same author

Factors Influencing Four Rules For Determining The Number Of Components To Retain.

Multivariate behavioral research·2016
Same author

An Empirical Comparison Of The Similarity Of Principal Component, Image, And Factor Patterns.

Multivariate behavioral research·2016
Same author

A Comparison Of Component And Factor Patterns: A Monte Carlo Approach.

Multivariate behavioral research·2016
Same author

Computer Programs for Interrupted Time Series Analysis: II A Quantitative Evaluation.

Multivariate behavioral research·2016
Same author

An Empirical Comparison of Factor, Image, Component, and Scale Scores.

Multivariate behavioral research·2016
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal
06:45

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Published on: April 18, 2017

6.7K

Computer Programs for Interrupted Time Series Analysis: I. A Qualitative Evaluation.

J W Harrop, W F Velicer

    Multivariate Behavioral Research
    |January 23, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study evaluates five computer programs for interrupted time series analysis, a method for longitudinal experiments. The evaluation focuses on computational features, documentation, and processing time to aid researchers in selecting appropriate software.

    More Related Videos

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
    13:00

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

    Published on: January 23, 2017

    10.4K
    Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
    07:12

    Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

    Published on: August 26, 2016

    10.0K

    Related Experiment Videos

    Last Updated: Mar 26, 2026

    Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal
    06:45

    Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

    Published on: April 18, 2017

    6.7K
    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
    13:00

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

    Published on: January 23, 2017

    10.4K
    Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
    07:12

    Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

    Published on: August 26, 2016

    10.0K

    Area of Science:

    • Statistics
    • Biostatistics
    • Health Services Research

    Background:

    • Interrupted time series analysis is crucial for evaluating interventions in longitudinal studies.
    • Data dependency in these studies requires specialized computer programs for accurate analysis.
    • Selecting the right software is essential for reliable research outcomes.

    Purpose of the Study:

    • To evaluate five recently developed computer programs for interrupted time series analysis.
    • To compare these programs based on key characteristics relevant to researchers.
    • To provide guidance on software selection for longitudinal data analysis.

    Main Methods:

    • Evaluation of five interrupted time series analysis programs: BMDP, GENTS, ITSE, SAS, and TSX.
    • Assessment criteria included computational features, documentation quality, and CPU time.
    • Comparative analysis of program performance and usability.

    Main Results:

    • The study provides a comparative overview of the evaluated software.
    • Differences in computational efficiency, documentation clarity, and resource requirements were identified.
    • Specific strengths and weaknesses of each program are highlighted.

    Conclusions:

    • The evaluation offers practical insights for researchers using interrupted time series analysis.
    • Informed software selection can enhance the efficiency and accuracy of longitudinal data analysis.
    • This comparison aids in choosing the most suitable program based on project needs and resources.