Analyse-it

Last updated
Analyse-it
Developer(s) Analyse-it Software, Ltd.
Stable release
5.11 / 2.30 (Win) / 2018
Operating system Windows
Type Statistical analysis
License Proprietary
Website analyse-it.com

Analyse-it is a statistical analysis add-in for Microsoft Excel. Analyse-it is the successor to Astute, developed in 1992 for Excel 4 and the first statistical analysis add-in for Microsoft Excel. Analyse-it provides a range of standard parametric and non-parametric procedures, including Descriptive statistics, ANOVA, ANCOVA, Mann–Whitney, Wilcoxon, chi-square, correlation, linear regression, logistic regression, polynomial regression and advanced model fitting, principal component analysis, and factor analysis.

Contents

Analyse-it Method Validation edition provides the standard Analyse-it statistical analyses above, plus procedures for method evaluation, validation and demonstration, including Bland–Altman bias plots, Linear regression, Weighted Linear regression, Deming regression, Weighted Deming regression and Passing Bablok for method comparison, Precision, Linearity, Detection limits, Reference intervals and Receiver operating characteristic analysis supporting Delong, Delong Clarke-Pearson comparisons.(see references below). Version 4.00 added support for CLSI guidelines EP5-A3, EP6-A, EP9-A3, EP10-A3, EP12-A2, EP15-A3, EP17-A2, EP21-A, EP24-A2 (formerly GP10-A), and EP28-A3C (formerly C28-A3C).

Analyse-it Quality Control & Improvement edition provides the standard Analyse-it statistical analyses above, plus procedures for statistical process control, including Shewhart, Levey-Jennings, CUSUM, and EWMA control charts, process capability analysis, and pareto analysis.

Analyse-it is compatible with Microsoft Excel 2007, 2010, 2013 and 2016 (Office 365) (both 32- and 64-bit versions).

Screenshots from Analyse-it

See also

Related Research Articles

<span class="mw-page-title-main">Meta-analysis</span> Statistical method that summarizes data from multiple sources

A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. It is thus a basic methodology of Metascience. Meta-analytic results are considered the most trustworthy source of evidence by the evidence-based medicine literature.

In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise. Robust regression methods are designed to limit the effect that violations of assumptions by the underlying data-generating process have on regression estimates.

<span class="mw-page-title-main">Bland–Altman plot</span> Data visualization

A Bland–Altman plot in analytical chemistry or biomedicine is a method of data plotting used in analyzing the agreement between two different assays. It is identical to a Tukey mean-difference plot, the name by which it is known in other fields, but was popularised in medical statistics by J. Martin Bland and Douglas G. Altman.

In statistics, resampling is the creation of new samples based on one observed sample. Resampling methods are:

  1. Permutation tests
  2. Bootstrapping
  3. Cross validation
<span class="mw-page-title-main">Local regression</span> Moving average and polynomial regression method for smoothing data

Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS and LOWESS, both pronounced. They are two strongly related non-parametric regression methods that combine multiple regression models in a k-nearest-neighbor-based meta-model. In some fields, LOESS is known and commonly referred to as Savitzky–Golay filter.

<span class="mw-page-title-main">MedCalc</span>

MedCalc is a statistical software package designed for the biomedical sciences. It has an integrated spreadsheet for data input and can import files in several formats.

The Unistat computer program is a statistical data analysis tool featuring two modes of operation: The stand-alone user interface is a complete workbench for data input, analysis and visualization while the Microsoft Excel add-in mode extends the features of the mainstream spreadsheet application with powerful analytical capabilities.

NCSS is a statistics package produced and distributed by NCSS, LLC. Created in 1981 by Jerry L. Hintze, NCSS, LLC specializes in providing statistical analysis software to researchers, businesses, and academic institutions. It also produces PASS Sample Size Software which is used in scientific study planning and evaluation.

In statistics, regression validation is the process of deciding whether the numerical results quantifying hypothesized relationships between variables, obtained from regression analysis, are acceptable as descriptions of the data. The validation process can involve analyzing the goodness of fit of the regression, analyzing whether the regression residuals are random, and checking whether the model's predictive performance deteriorates substantially when applied to data that were not used in model estimation.

<span class="mw-page-title-main">Plot (graphics)</span>

A plot is a graphical technique for representing a data set, usually as a graph showing the relationship between two or more variables. The plot can be drawn by hand or by a computer. In the past, sometimes mechanical or electronic plotters were used. Graphs are a visual representation of the relationship between variables, which are very useful for humans who can then quickly derive an understanding which may not have come from lists of values. Given a scale or ruler, graphs can also be used to read off the value of an unknown variable plotted as a function of a known one, but this can also be done with data presented in tabular form. Graphs of functions are used in mathematics, sciences, engineering, technology, finance, and other areas.

Psychometric software is software that is used for psychometric analysis of data from tests, questionnaires, or inventories reflecting latent psychoeducational variables. While some psychometric analyses can be performed with standard statistical software like SPSS, most analyses require specialized tools.

Seed-based d mapping or SDM is a statistical technique created by Joaquim Radua for meta-analyzing studies on differences in brain activity or structure which used neuroimaging techniques such as fMRI, VBM, DTI or PET. It may also refer to a specific piece of software created by the SDM Project to carry out such meta-analyses.

The following outline is provided as an overview of and topical guide to regression analysis:

In statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model. To combat this, model validation is used to test whether a statistical model can hold up to permutations in the data. This topic is not to be confused with the closely related task of model selection, the process of discriminating between multiple candidate models: model validation does not concern so much the conceptual design of models as it tests only the consistency between a chosen model and its stated outputs.

PSI-Plot is a scientific and engineering data analysis and technical plotting software developed by Poly Software International, Inc. The software can read multiple formats and perform mathematical transforms and statistical analyses. PSI-Plot is maintained on Microsoft Windows operating systems, and the current version is 9.5 for Windows 98 to Windows 7.

<span class="mw-page-title-main">JASP</span> Free and open-source statistical program

JASP is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS. It offers standard analysis procedures in both their classical and Bayesian form. JASP generally produces APA style results tables and plots to ease publication. It promotes open science via integration with the Open Science Framework and reproducibility by integrating the analysis settings into the results. The development of JASP is financially supported by several universities and research funds. As the JASP GUI is developed in C++ using Qt framework, some of the team left to make a notable fork which is Jamovi which has its GUI developed in Javascript and HTML5.

Passing–Bablok regression is a method from robust statistics for nonparametric regression analysis suitable for method comparison studies introduced by Wolfgang Bablok and Heinrich Passing in 1983. The procedure is adapted to fit linear errors-in-variables models. It is symmetrical and is robust in the presence of one or few outliers.

In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables. The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.

References