# Specifications

## Contents:

## Core Features

- 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. bootstrap around 100 times faster than R) - Can link easily with Microsoft
**Excel** - Delivered and supported directly via the
**web** - Designed for both front line
**research**and**education** - Built upon twenty years of research and development

## Data Import and Export

- Workbooks (similar to Excel spreadsheet)
- Maximum worksheet capacity is 64K columns by 1M rows
- Read and write Microsoft Excel files (2013/2010/2007 or 97-2003)
- Import any common spreadsheet data
- Import text based data (formatted or plain)
- Read/write reports in portable rich text format (RTF) or HTML
- Windows metafile scaleable graphics (can edit components in Word)

## Help

- Statistics guide/text on-line
- Comprehensive scientific references for methods
- Context-sensitive help with results/reports
- Powerful educational tool
- Global academic user base

## Data Preparation

- On-line algebraic calculator
- Apply user-defined functions/formulae to data in worksheet
- Many arithmetic, trigonometric, algebraic and logical functions
- Sort in worksheet (like Excel) or as separate function
- Rotate/transpose blocks of data in worksheet
- Ranks and normal scores (van der Waerden, Blom and expected normal order)
- Combine or split data by group identifier or separate columns
- Transformations (many, including ladder of powers)
- Standardization
- Anthropometric standardization (child growth charts)
- All pairwise differences, means and slopes
- Dummy/design/indicator variable generation
- Convert text to numbers
- Generate random numbers (uniform, normal, chi-square, F, t, binomial, Poisson, gamma, exponential)
- Categorise a continuous variable
- Extract a subset of data by search rules
- Tabulate and detabulate row/column classified data

## Descriptive Statistics

- Univariate descriptive statistics (count, mean, standard deviation, standard error, confidence interval, skewness, kurtosis, median, quartiles, range and a user defined quantile)
- Frequencies
- Tabulations and crosstabs
- Time series summary with area under time-concetration curve for pharmacokinetics

## Confidence Intervals

- Strong emphasis on confidence interval inference
- Exact (profile likelihood) methods used wherever practical
- Additional mid-P coverage given with many intervals
- Help on interpretation

## Graphics/Charts/Plots

- Bar/column charts
- Frequency distribution histograms
- Spread plots, dotplots
- Box & whisker plots
- Normal plots, nomal scores
- Forest (Cochrane, 'blobogram') plots
- Scatter plots, line charts and error bar plots
- Ladder, pairwise change plots
- Agreement plots
- Survival curves
- Residual and diagnostic plots with regressions
- Area under ROC curves
- Population pyramids
- Control (statistical process) charts

## Parametric Methods

- Student's t tests for single, paired (including agreement stats) and unpaired samples
- Normal distribution (Z) tests
- Reference range (normal, log-normal and percentile-based)
- F test, variance ratio test
- Shapiro-Wilk, Shapiro-Francia and Royston tests for (non) normality

## Non-parametric Methods

- Exact P values and confidence intervals
- Mann-Whitney (Wilcoxon rank sum)
- Wilcoxon signed ranks
- Spearman and Kendall rank correlations
- Cuzick's test for trend
- Two sample Smirnov
- 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 goodness of fit
- Gini coefficient of inequality with bootstrap confidence intervals
- Simpson and Shannon diversity indices with bootstrap confidence intervals
- LOESS curve fitting
- Nonparametric linear regression

## Regression and Correlation

- Simple linear regression and Pearson's correlation
- Multiple/general linear with best subset selection
- Principal components analysis (PCA) with Cronbach's alpha
- Influential data identification, residual diagnostics and plots
- Grouped 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 back interpolation
- Logistic regression with confidence intervals for cross classification and odds ratios, and bootstrap
- Conditional logistic regression for matched case-control studies
- Poisson regression, relative risk, incidence rate ratio
- Curve fitting
- Cox regression, proportional hazards, hazard ratio
- Kendall and Spearman rank correlations with confidence intervals

## Analysis of Variance

- Randomized Block: one way, two way, two way with repeats
- Multiple comparisons: Tukey(-Kramer), Dunnett, Neuman-Keuls, ScheffĂ© and Bonferroni
- Nonparametric: Kruskal-Wallis and Friedman with multiple contrasts
- Crossover
- Latin squares
- Nested/Hierarchical two way
- Homogeneity of variance
- Analysis of agreement

## Agreement Analysis

- Agreement of continuous data (intra-class correlation etc.)
- Agreement of categorical data (kappa or two or more raters and two or more categories etc.)
- Reliability and reducibility (Cronbach's alpha for scale reliability etc.)
- Berry-Mielke Universal R

## Meta-analysis

- Exact pooled estimates given wherever practical
- Odds ratio
- Peto odds ratios
- Relative risk
- Risk difference
- Effect size (d, g)
- Incidence rate difference and ratio
- Proportion
- Correlation
- Summary data meta-analysis
- Forest plots and exact confidence intervals
- L'AbbĂ© plots
- Funnel plots
- Egger et al. and Begg & Mazumdar bias tests
- I-square confidence intervals and heterogeneity summary

## Survival Analysis

- Kaplan-Meier estimates with survival plots
- Confidence intervals for mean and median survival times
- Follow-up (Berkson-Gage) life tables
- Abridged current life tables
- Logrank test with trend, exact hazard ratios, stratified
- Generalized Wilcoxon tests (Peto-Prentice, Gehan-Breslow or Tarone-Ware weights)
- Wei-Lachin multivariate comparison of two groups
- Cox regression, proportional hazards, multivariate hazard ratio

## Distribution Functions

- Normal, Gaussian
- Student t
- F
- Chi-square
- Studentized range Q
- Binomial
- Poisson
- Spearman rho
- Kendall tau
- Non-central t
- Gamma
- Many other distribution functions behind other methods: hypergeometric, Kolmogorov-Smirnov, Mann-Whitney U etc.

## Chi-square Contingency Tables

- 2 by 2 with confidence interval for odds ratio or relative risk
- 2 by K with trend
- R by C with trend and G square
- McNemar matched pairs (and k by k extension)
- Maxwell (agreement, equivalence)
- Mantel-Haenszel and Woolf with plots
- Generalised Cohrane-Mantel-Haenszel for R by C by K tables
- Goodness of fit

## Exact Tests on Counts

- Fisher exact (2 by 2 tables)
- Fisher-Irwin (R by C tables)
- Gart confidence intervals for odds ratios
- Liddell exact alternative to McNemar for matched pairs
- Sign test, binomial test
- Poisson rate or count confidence interval

## Proportions

- Single
- Paired
- Two independent
- Exact confidence intervals

## Rates

- Exact Poisson confidence intervals for rates or counts
- Exact analysis of rate ratios
- Direct standardization
- Indirect standardization and standardized mortality ratio (SMR)
- Standardize and compare two rates
- Incidence rate meta-analysis

## Sample Size Estimation

- For comparison of means (paired, unpaired)
- For comparison of proportions
- For population surveys
- For survival analysis
- For correlation

## Randomization

- Uses robust random number generator (Mersenne-Twister)
- Intervention-control pairs (with balanced allocation)
- Allocation to independent intervention and control groups
- Block randomization
- Preference group allocation
- Random series of integers from X to Y
- Generate random numbers from distributions (uniform, normal, binomial, Poisson, beta, F, t, chi-square, gamma, lognormal, Cauchy, Weibull, exponential, logistic, negative binomial) for simulation

## Clinical Epidemiology

- Prospective risk: relative risk, risk reduction and population attributable risk
- Retrospective risk: odds ratio, population attributable risk
- Diagnostic test analysis
- Likelihood ratios in diagnostic test series
- Number needed to treat (NNT) with exact confidence intervals
- Screening test error probabilities (Bayes)
- Kappa (optional user defined weights) and Scott's pi agreement
- Incidence rate analysis
- Growth charts (anthropometric z-scores)

## System Requirements

- Any version of Microsoft Windows running .Net version 4 or later, including XP (with Service Pack 3), Vista, 7, 8, 8.1 and 10
- 32-bit or 64-bit Windows (bigger datasets and faster on 64-bit)
- At least 1GB memory free
- Some users run StatsDirect on a Mac with Microsoft Windows installed using virtualisation (e.g. via Vmware Fusion or Parallels)
- Previous StatsDirect version 2 is available for old Windows NT, 2000 or XP before Service Pack 3

## Availability

Available for purchase via the web.

Official orders taken from academia, public sector and corporations.

Special pricing for individuals, students and developing world.

Third party tutorials such as learning with StatsDirect are available.