StatsDirect

What is StatsDirect?

Key Features of StatsDirect

Exceptionally easy to use

Statistics guide built into the software

Includes all common statistical methods

State-of-the-art computational methods for fast and reliable results (e.g., auto-initialization about 100 times faster than R)

Can easily connect with Microsoft Excel

Delivered and supported directly via the web

Designed for frontline research and education

Data Import and Export

Workbooks (similar to Excel worksheet)

The maximum capacity of the spreadsheet is 64K columns per 1M rows

Read and write Microsoft Excel files (2013/2010/2007 or 97-2003)

Import all common worksheet data

Import text-based data (formatted or plain label)

Read/write reports in RTF (Portable Rich Text Format) or HTML format

Scalable graphics from Windows metafiles (can edit components in Word)

Data preparation with StatsDirect

Online algebraic calculator

Apply user-defined functions/formulas to the data in the worksheet

Many arithmetic, trigonometric, algebraic, and logical functions

Sort on worksheet (such as Excel) or as a separate function

Rotate/transpose blocks of data in the worksheet

Normal classification and scoring (van der Waerden, Blom and expected normal order)

Combine or divide data by group identifier or separate columns

Transformations (many, including ladder of powers)

standardization

Anthropometric standardization (child growth charts)

All differences, averages and slopes to pairs

Generation of dummy variables / design / indicator

Convert text to numbers

Generate random numbers (uniform, normal, chi-squared, F, t, binomial, Poisson, gamma, exponential)

Categorize a continuous variable

Extract a subset of data by search rules

Tabulate and disassemble row/column sorted data

Descriptive statistics

Univariate descriptive statistics (count, mean, standard deviation, standard error, confidence interval, asymmetry, kurtosis, median, quartiles, interval, and user-defined quantile)

Frequencies

Tabs and crosstabs

Summary of time series with area under time conception curve for pharmacokinetics

StatsDirect confidence intervals

Strong emphasis on confidence interval inference

Exact methods (profile probability) used whenever possible

Additional P-medium coverage provided with many intervals

Interpretation help

StatsDirect Charts

Bar/column charts

Frequency distribution histograms

Spread plots, dotplots

Box and whisker charts

Normal plots, nomadic scores

Forest plots (Cochrane, 'blobogram')

Scatter charts, line charts, and error bar charts

Ladder, pairwise alteration plots

Contract installments

Survival curves

Residual and diagnostic graphs with regressions

Area under ROC curves

Population pyramids

Control charts (statistical process)

Parametric methods

Student's t-tests for single, paired (including agreed-in statistics) and unpaired samples

Normal distribution tests (Z)

Reference range (normal, log-normal, and percentile-based)

F-test, ratio of variance test

Shapiro-Wilk, Shapiro-Francia and Royston tests for (non)normality

Nonparametric methods

Exact P values and confidence intervals

Mann-Whitney (sum of Wilcoxon classification)

Wilcoxon classification

Spearman and Kendall classify the correlations

Cuzick test for trend

Smirnov of two samples

Exact confidence intervals for median and other centiles

Homogeneity of variance, including Breslow-Day test

Friedman, Cochrane Q, Kruskal-Wallis with multiple contrasts

Chi-square fit quality

Gini inequality coefficient with self-initialization confidence intervals

Simpson and Shannon diversity indices with initialization confidence intervals

LOESS curve adjustment

Nonparametric linear regression

Regression and Correlation

Simple linear regression and Pearson correlation

Linear multiple/general with the best subset selection

Principal component analysis (PCA) with Cronbach's alpha

Identification of influential data, residual diagnosis and plots

Pooled linear regression with analysis of covariance

Various linearized estimates

Probit analysis (probit or logit), dose response, ED50, LD50

Polynomial regression with area under curve and rear interpolation

Logistic regression with confidence intervals for cross-classification and odds ratio and auto-initialization

Conditional logistic regression for paired case-control studies

Poisson regression, relative risk, incidence rate

Curve adjustment

Cox regression, proportional risks, hazard ratio

Kendall and Spearman classify correlations with confidence intervals

Analysis of variation

Random block: unidirectional, bidirectional, bidirectional with repetitions

Multiple comparisons: Tukey (-Kramer), Dunnett, Neuman-Keuls, Scheffé and Bonferroni

Nonparametric: Kruskal-Wallis and Friedman with multiple contrasts

Crossover

Latin squares

Nested / hierarchical in two senses

Homogeneity of variance

Analysis of agreement

Contract Analysis

Continuous data agreement (intra-class correlation etc.)

Categorical data agreement (kappa or two or more evaluators and two or more categories, etc.)

Reliability and reducibility (Cronbach's alpha for scale reliability, etc.)

Meta-analysis

Exact estimates pooled where possible

Probability ratio

Relative risk

Risk difference

Effect size

Difference and ratio of the incidence rate

Proportion

Correlation

Summary meta-analysis of data

Exact forest plots and confidence intervals

Lots of L'Abbé

Funnel charts

I square confidence intervals and summary of heterogeneity

Survival Analysis

Kaplan-Meier estimates with survival plots

Confidence intervals for mean and median survival times

Follow-up Life Tables (Berkson-Gage)

Summarized current life tables

Logrank test with trend, exact risk ratios, stratified

Generalized Wilcoxon tests (Peto-Prentice, Gehan-Breslow or Tarone-Ware weights)

Multivariate Wei-Lachin comparison of two groups

Cox regression, proportional risks, multivariate hazard ratio

Distribution functions

Normal, Gaussian

Student t

F

Chi-square

Range studied Q

Binomial

Poisson

Spearman rho

Kendall tau

Non-central T

Range

Chi-square contingency tables

2 by 2 with confidence interval for odds ratio or relative risk

2 per K with trend

R by C with trend and square G

McNemar matching pairs (ek by extension k)

Maxwell (agreement, equivalence)

Mantel-Haenszel and Woolf with plots

Generalized Cohrane-Mantel-Haenszel tables for R by C by K tables

Fit quality

System Requirements

Any version of Microsoft Windows supported by Microsoft running the .Net Framework version 4.6.1 or later, including 7 (with Service Pack 1), 8, 8.1, and 10

32-bit or 64-bit Windows (larger, faster 64-bit datasets)

At least 1 GB of free memory

Some users run StatsDirect on a Mac with Microsoft Windows installed using virtualization (for example, via Vmware Fusion or Parallels)

Some users run StatsDirect on Windows server-class operating systems: 2008 R2, 2012, 2012 R2, 2016, 2019

Previous version 2 of StatsDirect is available for Windows NT, 2000, XP, Vista, or older 7, without Service Pack 1