Ultimate Edition

Every statistical tool we make, in one licence Method validation with 11 CLSI protocols, diagnostic accuracy with ROC curves, survival analysis with Kaplan–Meier and Cox regression, statistical process control with Shewhart, CUSUM, and EWMA charts, plus the full general statistics toolkit — ANOVA, regression, PCA, and more.

Every feature from all five editions for 15 days, no sign-up.
Ultimate edition from US$ 575 a year · 30-day money-back guarantee.

Most organisations don’t fit neatly into a single edition. The IVD company running CLSI method validation studies also needs SPC on the manufacturing line. The clinical lab verifying a new assay also runs survival analysis for research publications.

The quality team monitoring control charts also needs ANOVA and regression to investigate out-of-control events.

The Ultimate edition unlocks every feature across all four editions — Method Validation, Medical, Quality Control & Improvement, and Standard — in a single licence at US$575/yr, less than any two specialist editions bought separately. Already own a specialist edition? Upgrade for the difference in price.

We use Analyse-it frequently for our verification and pre-verification work, in accordance with CLSI guidelines for in-vitro diagnostics. It’s saved time and effort compared to the hodge-podge of applications we used before, JMP, SAS, etc…

Brian Noland, Ph.D.
Principal Scientist, Product Development
Biosite / Inverness Medical Innovations

Validate and verify measurement system performance

The complete CLSI method validation toolkit — precision, linearity, detection capability, method comparison, reference intervals, and diagnostic performance — with 11 evaluation protocols built in:

Precision with nested variance component designs — repeatability, between-run, between-day, within-laboratory and reproducibility — and precision profiles with seven variance function models (EP05-A3)
Linearity with polynomial and weighted regression, Hsieh-Liu nonlinearity testing against an allowable nonlinearity, and an adjustable measuring interval for reportable range determination (EP06-Ed2)
Detection capability — LoB, LoD and LoQ using parametric, non-parametric, probit regression and precision profile variance function approaches (EP17-A2)
Verification of precision and trueness against manufacturer claims — such as testing an observed CV against a claimed 3.5% — with χ² and equivalence tests (EP15-A3), and preliminary evaluation of precision and bias at three levels against allowable limits (EP10-A3-AMD)

Measurement system analysis details →

The CA19-9 precision profile: CV against concentration for repeatability, within-laboratory precision and reproducibility, with the fitted 3-parameter variance function and its parameters for each.

Compare methods and evaluate the impact of changes

Five regression models for method comparison — including Passing-Bablok, Deming, and weighted Deming — plus Bland–Altman agreement and total analytical error:

Passing-Bablok and Deming and Weighted Deming regression with confidence intervals on the slope and intercept, and bias at medical decision points with equality and equivalence tests against an allowable difference
Bland–Altman limits of agreement — the bias as a mean, a median or a regression across the measuring range, with constant or non-constant precision and confidence intervals on the limits
Total analytical error per EP21-A — bias and imprecision combined and judged against the allowable total error, with the mountain plot of the differences
Commutability of processed samples and reference materials per EP14-A3 — compared against patient samples with prediction intervals
Qualitative methods — positive and negative agreement, and kappa and weighted kappa with linear or quadratic weights, for two methods with no known true state (EP12-A2)

Method comparison details →

Microsoft Excel showing a method comparison report for LDL cholesterol: the Bland-Altman difference plot with the 95% limits of agreement and the allowable difference band, with the task pane open on Fit Differences. Handwritten notes: Difference plot: Y - X against X; 95% limits of agreement and the allowable difference band; Bias model: mean, median or linear fit; limits.

LDL cholesterol, 100 samples, from EP21-A Table 2: the difference plot with the 95% limits of agreement and the ±10 mg/dL allowable difference band.

Establish reference intervals for clinical interpretation

Full range of reference interval methods — match the method to your sample size and distribution, partition where subgroups need separate ranges, and transfer or verify intervals when moving to a new measurement procedure:

Five quantile methods — parametric, non-parametric (three computation approaches), robust bi-weight, bootstrap and Harrell–Davis — the right estimator for the sample size and the shape of the data
Partition by sex, age, ethnicity or any combination of factors — one report per partition, with the descriptive statistics and limits for each
Full range of transformations — log, square root, cube root, Box–Cox, Manly exponential, two-stage exponential/modulus — for skewed analytes, with the limits reported back in the original units
Transfer and verify existing intervals — a published interval checked against 20 samples with the binomial proportion test, or transferred by regression between procedures

Reference interval details →

Microsoft Excel showing a reference interval report for ALT in females: the raw histogram with its reference limits, and beneath it the Transformed histogram of ln ALT with a normal curve overlaid, with the task pane open on the Transform section. Handwritten notes: Raw ALT: skewed, with its reference limits; The same data after a log transform, normal curve overlaid; Transform: log, Box-Cox, Manly or two-stage modulus.

ALT in females: the raw histogram with its reference limits, and beneath it the same data after a natural log transformation with the normal curve overlaid.

Evaluate diagnostic test accuracy

Establish and compare the ability of a diagnostic test to discriminate between patients with and without a condition — and find the decision threshold that balances sensitivity, specificity, and clinical cost:

Empirical ROC curves per EP24-A2, with the area under the curve, its DeLong confidence interval and the test against no discrimination
AUC comparison (DeLong) for up to 10 paired or independent tests — the difference in AUC with its confidence interval, and equality, equivalence or non-inferiority hypotheses
Sensitivity, specificity, likelihood ratios, predictive values at a prior probability, and the diagnostic odds ratio — each with its confidence interval
Optimal decision threshold by Youden’s index, the point closest to (0,1), or the clinical costs of misdiagnosis — and the sensitivity and specificity at any threshold
Qualitative test evaluation per EP12-A2 — sensitivity and specificity with confidence intervals, and the difference between two tests, for a test read as positive or negative against a known state

Diagnostic performance details →

Microsoft Excel showing the ROC Curve section of a diagnostic performance report: ROC curves for OxLDL and LDL, and the AUC table with DeLong 95% confidence intervals, SE, Z statistic and p-value for each test, with the task pane open on ROC Curve. Handwritten notes: ROC curve for each test; AUC with DeLong 95% CI, Z test and p-value; AUC estimator, CI and method.

ROC curves for OxLDL and LDL on one chart, and the AUC of each test with its DeLong 95% confidence interval, standard error, Z statistic and p-value.

Analyse time-to-event data with survival analysis

Estimate survival functions, compare treatment groups, and model the effect of covariates on the hazard:

Kaplan–Meier survival curve for each group with pointwise, Nair or Hall–Wellner confidence bands, and the censored observations marked on the curve
Median, quartile and restricted mean survival time for each group, each with its confidence interval, and the survival function as a table
Test equality of the survival functions with the log-rank, Wilcoxon, Tarone–Ware or Fleming–Harrington test — the weighting chosen for early or late differences
Cox proportional hazards regression — the hazard ratio for every term with its confidence interval, interactions between factors, and the baseline survival function

Survival analysis details →

Microsoft Excel showing a survival analysis report: Kaplan-Meier survival curves for three tumour grades with censored observations marked, and the N, events, mean and median tables beneath, with the task pane open on the survival function options. Handwritten notes: A survival curve for each tumour grade; N, events, mean and median survival; Band: pointwise, Nair or Hall-Wellner.

Kaplan–Meier survival curves for the same 30 brain cancer patients grouped by tumour grade, censored observations marked on each curve.

Monitor processes with control charts

Shewhart variable and attribute charts with automatic detection rules, plus time-weighted charts for detecting small, sustained shifts:

Xbar-R, Xbar-S and I-MR charts for continuous data; p, np, c and u charts for attribute data — limits from the data or from known process parameters
CUSUM, EWMA and UWMA time-weighted charts — for the small, sustained shifts that a Shewhart chart is slow to signal, with the decision interval or weight set in the task pane
WECO, Nelson and Montgomery detection rules, or a custom set — runs, trends, stratification and oscillation flagged automatically, each signal labelled with the rule it broke
Phases for before-and-after comparison — installation, qualification and production, say — each with its own control limits on the one chart
Stratification by operator, shift, machine, material lot or any factor — points coloured and labelled by the factor, so the cause of a signal is visible on the chart

Control chart details →

Microsoft Excel showing the Control section of a process control report for copper concentration: the EWMA chart with weight 0.2 and 3-sigma limits across the OQ and Production phases, the out-of-control point on 23/01 flagged, the R chart beneath, and the Process Control task pane open on the EWMA chart section. Handwritten notes: EWMA chart across the phases, with the signals flagged; R chart beneath; EWMA: weight lambda and limit width L.

EWMA chart (λ = 0.2, L = 3) of copper concentration with the R chart beneath, across the OQ and Production phases: one signal on 23/01.

Determine whether the process meets the specification

Capability and performance indices with confidence intervals and non-normal data handling:

Cp, Cpk and Cpm for the inherent capability of a stable process; Pp and Ppk for the performance actually delivered — each with a confidence interval, so a marginal index is read as such
Z-benchmark and sigma level, and the nonconforming units outside each specification limit — observed %, expected % and expected PPM
Box-Cox and power transformations for non-normal distributions — so the indices are computed on data that meet the assumption behind them
Histogram with the specification limits and a fitted normal curve, and a normal Q-Q plot with Lilliefors band — see whether the process is centred, and whether the data are normal

Capability analysis details →

Microsoft Excel showing the Capability section of a process capability report: specification limits 7 to 11, mean and long-term sigma, the Pp, Ppl, Ppu and Ppk indices with 95% confidence intervals, observed and expected nonconforming units in PPM, and the Z benchmark table. Handwritten notes: Pp, Ppl, Ppu and Ppk with 95% CIs; Expected nonconforming units, PPM; Z-benchmark.

The Capability section for copper concentration in a plating pool: Pp, Ppl, Ppu and Ppk with 95% confidence intervals, the nonconforming unit estimates and the Z-benchmark beneath.

Focus improvement effort on the vital few

Pareto charts to identify the most frequently occurring defects and break them down by contributing factors:

One-way and two-way comparative Pareto charts — defect type by operator, shift, machine or product line, one chart per cell so the vital few in each are compared side by side
Merge low-frequency categories into one bar, reorder the bars by any key, and colour by subgroup — the categories table in the task pane, no data editing
Cumulative percentage line with each point labelled — the 80/20 cut-off read straight off the chart, bars labelled with their frequencies

Pareto analysis details →

Microsoft Excel showing a two-way comparative Pareto chart: a row of Pareto panels for each of the operators GMH, JDH and SNH, a column for before and after training, each panel with its cumulative percentage line, and the failure category legend, with the Pareto task pane open. Handwritten notes: One Pareto chart per cell: operator by training; Layout: matrix.

Two-way comparative Pareto chart: colorimeter failures for each of three operators, before and after training.

Compare groups and test for differences

Independent samples, paired samples, two groups or ten — parametric and non-parametric tests with the assumption checks built into the same workflow:

Student’s t, Welch’s t and Wilcoxon-Mann-Whitney for two independent groups; one-way ANOVA, Welch’s ANOVA and Kruskal-Wallis for three or more — with the homogeneity of variance tests that decide between them
Paired t-test, Wilcoxon signed ranks and Sign test for two related measurements; within-subjects ANOVA and Friedman for repeated measures on three or more occasions
Eight multiple comparison procedures — Tukey-Kramer, Dunnett, Hsu, Scheffé, Steel, Dwass-Steel-Critchlow-Fligner among them — to find which groups differ after a significant ANOVA, each controlling the family-wise error rate
Cohen’s d and Hedges’ g effect sizes with non-central t confidence intervals — how large the difference is, not only whether it is significant

Hypothesis testing details →

Microsoft Excel showing a Compare Pairs report for body fat before and after an exercise programme: side-by-side box plots with a line joining each of the 28 pairs, the descriptive statistics for Before, After and the differences beneath, and the Compare Pairs task pane open on Descriptives. Handwritten notes: Before and after for each subject, joined; box plots for each measure; Descriptives of the pairs and their differences; Connect the pairs.

Body fat before and after an exercise programme, 28 pairs: box plots with a line for each pair, and the descriptive statistics for Before, After and the differences.

Fit and diagnose regression models

Regression as a process of building, examining, and refining — not a single pass from data to p-value:

Simple linear, polynomial, logarithmic, exponential, power and probit regression — fit the curve the relationship calls for, with a confidence band on the fit
Multiple regression with continuous and categorical predictors, crossed terms and interactions — categorical predictors are dummy-coded automatically, one row per level in the estimates
Binary logistic regression for a yes/no outcome — the odds ratio for every predictor with its Wald confidence interval, and likelihood ratio tests for the model and each term
ANOVA and ANCOVA with crossed factors, interactions and continuous covariates — effect means, main effect and interaction plots, and multiple comparisons on the effect means
Residual diagnostics, leverage plots, Cook’s D influence and VIF for multicollinearity — the checks that show whether a model can be trusted before it is reported

Regression details →

Microsoft Excel showing the Outliers, Leverage, Influence section of a multiple regression report of pulse rate on eight predictors: studentised residuals plotted against leverage for 109 observations, bubble size Cook's D, with the unusual cases labelled by observation number, and the Fit Model task pane open on the Outliers section. Handwritten notes: Studentised residual against leverage, bubble size Cook's D; influential cases labelled; Plot type, and labelling of influential cases.

Studentised residual against leverage for the 109 pulse-rate observations, bubble size Cook’s D, with the unusual cases labelled by observation number.

Describe and visualise data

Every analysis starts with understanding the data. What does the distribution look like? Are there outliers? Is it normal?

Mean, median, SD, CV%, skewness, kurtosis, geometric mean, harmonic mean, quantiles and mode — the location and dispersion of a variable, with confidence intervals, in one table
Histograms, dot plots, box plots (skeletal, Tukey outlier, quantile), CDF plots and Q-Q plots with Lilliefors bands — see the shape of the distribution, and any outliers, before choosing a test
Shapiro-Wilk, Anderson-Darling and Kolmogorov-Smirnov normality tests — a formal check on the assumption behind a t-test or ANOVA, alongside the Q-Q plot
Correlation — Pearson r, Spearman r_s and Kendall τ for every pair of variables, each with a confidence interval and test, and colour-mapped matrices to see the relationships
PCA and common factor analysis — reduce many correlated variables to a few components or factors, with Gabriel and Gower-Hand biplots and 12 orthogonal and oblique rotation methods

Descriptive statistics details →

Microsoft Excel showing the Frequencies section of a discrete distribution report for the eye colour of 592 people: the bar plot of relative frequency for brown, blue, hazel and green, the pie plot beneath it, the frequency table, and the Distribution task pane open. Handwritten notes: Frequency bar chart with the cumulative relative frequency line; Whole-to-part pie chart, sectors labelled; Plot: bar or pie, with the cumulative line.

Eye colour of 592 people: the bar plot of relative frequency and the pie plot from the discrete distribution report, with the task pane open.

We use Analyse-it for the analysis of data necessary to file 510k. We chose Analyse-it because it works in Excel, includes CLSI protocols, and, unlike EP-Evaluator, lets us analyze data directly from equipment without typing.

Thomas D Harrigan, Ph.D.
Technical Product Manager
Alfa Wassermann Diagnostic Technologies

Everything, in one licence

The Ultimate edition includes every feature from the Method Validation, Medical, Quality Control & Improvement, and Standard editions. If your organisation needs capabilities from more than one specialist edition — or you don’t want to have to choose — Ultimate is the simpler and cheaper option. You’ve already been using every feature during the 15-day trial.

Validated, reliable, trusted for nearly 30 years

Validated calculations Every statistic tested against the NIST Statistical Reference Datasets, published datasets and thousands of internal test cases. No reliance on Excel’s built-in functions. See how we develop and validate Analyse-it →

Data stays on your PC No cloud processing, no uploads, no third-party access. Your data never leaves your computer — essential when working with sensitive, confidential, or patient-identifiable data.

Standard Excel workbooks Analyses are ordinary Excel workbooks that you can share with colleagues, archive for audit, and open on any machine with Excel — no Analyse-it licence required.

No formulas to break Results contain no formulas, so they cannot be accidentally edited or corrupted. The results you reported will be exactly what you find when you reopen the workbook.

Support for 11 CLSI protocols

The latest Clinical and Laboratory Standards Institute (CLSI) method validation protocols are recognised by the College of American Pathologists (CAP), The Joint Commission, and the US Food and Drug Administration (FDA).

EP05-A3	Evaluation of Precision of Quantitative Measurement Procedures	Precision
EP06-Ed2	Evaluation of the Linearity of Quantitative Measurement Procedures	Linearity
EP09-A3	Measurement Procedure Comparison and Bias Estimation Using Patient Samples	Method comparison
EP10-A3-AMD	Preliminary Evaluation of Quantitative Clinical Laboratory Measurement Procedures	MSA
EP12-A2	User Protocol for Evaluation of Qualitative Test Performance	Diagnostic performance
EP14-A3	Evaluation of Commutability of Processed Samples	Method comparison
EP15-A3	User Verification of Precision and Estimation of Bias	MSA
EP17-A2	Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures	Detection capability
EP21-A	Estimation of Total Analytical Error for Clinical Laboratory Methods	Method comparison
EP24-A2	Assessment of the Diagnostic Accuracy of Laboratory Tests Using Receiver Operating Characteristic Curves	Diagnostic performance
EP28-A3C	Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory	Reference intervals

I used Analyse-It for many product development, product troubleshooting, and technology evaluation activities… your product was the easiest to use, was accurate, and produced publication ready reports.

Stanley F. Cernosek, Ph.D.
Clinical Chemistry Reagent Development
Beckman Coulter, Inc.

Analyse-it has been a tremendous help. I’ve published and presented at national cardiology meetings and couldn’t have accomplished most of my research without it. Using Analyse-it, I even found errors or omissions in the work of our statistician!

Regina S. Druz, MD, FACC, FASNC
Director, Nuclear Cardiology
North Shore University Hospital

Example analyses

Download example datasets, open them in the trial, and see exactly what the output looks like.

Method Validation

EP09-A3 — Appendix I
Difference plots over a partitioned interval. 79 observations split at 1.8 µg/L. Each interval gets its own difference plot, mean difference with a 95% CI, allowable difference and hypothesis test.

EP05-A2 — Appendix B
Glucose precision, single site. 20 days × 2 runs × 2 observations. Variability plot, variance components with CIs, and the ANOVA table.

EP28-A3C — Table 4
Calcium reference intervals by sex. 120 observations per sex. Nonparametric reference limits from the (N+1)p quantile with 90% CIs.

EP24-A2 — Appendix D
OxLDL and LDL diagnostic accuracy. 50 subjects. ROC curves with AUC and DeLong CIs, a DeLong comparison of the two curves, and a bi-histogram with a decision threshold plot.

Medical

Kaplan-Meier survival
Brain cancer survival, 30 patients. Two analyses of one dataset — survival by treatment, and survival by tumour grade over three groups. Survival curves with confidence bands, mean and median survival with CIs, and a log-rank test for each.

Quality Control & Improvement

Shewhart, EWMA and CUSUM
Copper concentration in a plating pool. Copper concentration across three phases. Xbar-R with Montgomery rules and operator stratification, plus EWMA and CUSUM on the same data.

Process capability
Copper concentration against a 7 to 11 ppm specification. Pp, Ppl, Ppu and Ppk with 95% CIs, a histogram against the specification limits, expected nonconforming units, and Z benchmarks.

Pareto analysis
Colorimeter downtime before and after training. A comparative Pareto stratified by operator and training status, and a Pareto for each training period with a cumulative line.

Standard

Continuous distribution
Newcomb’s speed of light, 64 observations. Descriptive statistics, frequency histogram, box and dot plot, cumulative distribution plot, normal Q-Q plot, Shapiro-Wilk test, and a one-sample t-test.

One-way ANOVA
Y by brand, 7 groups, 19 observations. Levene test for homogeneity of variance, one-way ANOVA, Tukey-Kramer over 21 contrasts, and a Mean-Mean scatter plot.

Simple regression, power fit
TV advertising budget against retained impressions. 21 observations. Power function fit with a 95% confidence band, parameter estimates with CIs, residual diagnostics, and an outlier, leverage and influence plot.

PCA and factor analysis
New York neighbourhood liveability, 12 variables. Eigenvalues and coefficients, a biplot labelled by borough, a correlation monoplot, and a common factor analysis with uniqueness, communality and factor loadings.

Free trial and pricing

Try it on your own data first. The 15-day trial is every feature from all five editions, with no sign-up and no licence key — install it and start straight away.

Download 15-day trial See pricing or get a quote →

Ultimate edition from US$ 575 per year, or US$ 1495 for a perpetual licence. Every purchase carries a 30-day money-back guarantee. Need a quote for purchasing? Add the licence to the cart and save it as a PDF quote.

Technical details

The Ultimate edition includes every feature from all four editions. Full technical specifications are on each edition’s page:

Method Validation edition — precision, linearity, detection capability, method comparison, reference intervals, diagnostic performance, 11 CLSI protocols
Medical edition — Bland–Altman agreement, diagnostic accuracy, reference intervals, survival analysis
Quality Control & Improvement edition — control charts, process capability, Pareto analysis
Standard edition — descriptive statistics, hypothesis tests, ANOVA/ANCOVA, regression, logistic regression, PCA, correlation, contingency tables

System requirements

Microsoft Excel 2013, 2016, 2019, 2021, 2024 and Microsoft 365 for Microsoft Windows (32- and 64-bit)
Microsoft Windows 8, 10, 11, Server 2016, 2019, 2022
2 GB RAM minimum recommended
80 MB disk space