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PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough. PASS lets you
solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal. PASS is a standalone system. Although it is integrated with
NCSS, you do not have to own NCSS to run it. You can use it with any statistical software you want. PASS 2008 runs under Windows Vista, XP, 2000, NT, ME, 98, and 95.
New Procedures:
Mixed Models
The Mixed Models procedure analyzes results from a wide variety of experimental designs in which the outcome (response) is
continuous, including
Twosample designs (replacing the ttest)
Oneway layout designs (replacing oneway ANOVA)
Factorial designs (replacing factorial GLM)
Splitplot designs (replacing splitplot GLM)
Repeatedmeasures designs (replacing repeatedmeasures GLM)
Crossover designs (replacing GLM)
Designs
with covariates (replacing GLM)
The Mixed Models procedure can be used to test and estimate means (including pairwise comparisons among levels), compare models, estimate variancecovariance matrix components, and produce graphs of means and repeated measurements of subjects. Restricted maximum likelihood and full maximum likelihood
techniques are implemented in thisprocedure.
Circular Data Analysis
This procedure computes summary statistics, generates rose plots and circular histograms, computes hypothesis tests appropriate for one, two, and several groups, and computes the circular correlation coefficient for circular data. Angular data, recorded in degrees
or radians, is generated in a wide variety of scientific research areas. Examples of angular (and cyclical) data include daily wind directions, ocean current directions, departure directions of animals, direction of bonefracture plane, and orientation of bees in a beehive after stimuli.
Data Matching Optimal and Greedy
This
procedure is used to create treatmentcontrol matches based on propensity scores and/or observed covariate variables. Both optimal and greedy matching algorithms are available (as two separate procedures), along with several options that allow the user to customize each algorithm for their specific needs. The user is able to choose the number
of controls to match with each treatment (e.g., 1:1 matching, 1:k matching, and variable (full) matching), the distance calculation method (e.g., Mahalanobis distance, propensity score difference, sum of rank differences, etc.), and whether or not to use calipers for matching. The user is also able to specify variables whose values must match
exactly for both treatment and controls in order to assign a match. NCSS outputs a list of matches by match number along with several informative reports and optionally saves the match numbers directly to the database for furtheranalysis.
Data Simulator
This procedure allows you to simulate, store, and visualize data from various
discrete and continuous distributions, including Beta, Binomial, Cauchy, Constant, Exponential, F, Gamma, Multinomial, Normal, Poisson, T, Tukeys Lambda, Uniform, and Weibull. Mixture distributions may also be simulated. This module creates a histogram of a specified distribution as well as a numerical summary of simulated data. By storing
the data, you can investigate the effects of varying data distributions on hypothesis tests and confidence intervals for your specific investigational situation.
Data Stratification
This procedure is used to create stratum assignments based on quantiles from a numeric stratification variable (often a propensity score variable). The
user is able to choose the number of strata to create and the amount of data used in the quantile calculations. Stratification is commonly used in theanalysis of data from observational studies where covariates are not controlled.
Double Dendrograms
Double dendrograms display clusters for individuals (rows) and variables (columns)
in a single graph. A set of eight hierarchical clustering algorithms are available including single linkage, complete linkage, and group average. Theprocedure outputs lists of the items in each cluster, linkage reports, and a doubledendrogram.
Merging Two Databases
Occasionally, it is useful to merge two databases according to the
value of one or more common (index) variables. This module allows you to merge two databases, or, alternatively, update one database with the contents of another.
Multiple Regression with Serial Correlation
This procedure uses the CochraneOrcutt method to adjust for serial correlation when performing multiple regression. The
regular Multiple Regression routine assumes that the randomerror components are independent from one observation to the next. However, this assumption is often not appropriate for business and economic data. Instead, it is more appropriate to assume that the error terms are positively correlated over time. Consequences of the error terms being
serially correlated include inefficient estimation of the regression coefficients, under estimation of the error variance (MSE), under estimation of the variance of the regression coefficients, and inaccurate confidence intervals. The presence of serial correlation can be detected by the DurbinWatson test and by plotting the residuals against
their lags.
Nondetects Analysis
This procedure computes summary statistics, generates EDF plots, and computes hypothesis tests appropriate for two or more groups for data with nondetects (leftcensored) values. Nondetects analysis is the analysis of data in which one or more of the values cannot be measured exactly because they fall
below one or more detection limits. Detection limits often arise in environmental studies because of the inability of instruments to measure small concentrations. Some examples of sampling scenarios that lead to datasets with nondetects values are finding pesticide concentrations in water, determining chemical composition of soils, or
establishing the number of particulates of a compound in the air.
Nondetects Regression
The nondetects regression procedure fits the regression relationship between a positivevalued dependent variable (with, possibly, some nondetected responses) and one or more independent variables. The distribution of the residuals (errors) is
assumed to follow the exponential, extreme value, logistic, loglogistic, lognormal, lognormal10, normal, or Weibull distribution. Nondetected responses occur when one or more of the values cannot be measured exactly because they fall below one or more detection limits.
New Tools:
Macros
NCSS has an interactive (point and
click) user interface which makes in easy to learn and use. At times, however, it is necessary to repeat the same steps over and over. When this occurs, a batch system becomes more desirable. Thisprocedure utilizes a batch language that lets you create a macro (script or program) and then run that macro. With the click of a single button, you
can have the program run a series of procedures.
Color Selection Windows
The color selection windows let you choose appropriate colors from the 16 million colors that are available on todays monitors. Although choosing a color sounds like a trivial task, it can become timeconsuming and frustrating. When you have invested a lot of
time and money in a project and now have important results to communicate, you probably want to take the time to make outstanding graphics. A few, wellchosen charts can communicate results quickly and effectively. An important feature of a chart is the color scheme that you use. The goal of the color selection window is to provide a tool that
will allow you to pick a set of colors that are pleasing to the eye when viewed together, and let the viewer interpret the results quickly and effectively.
Quick Launch Window
The Quick Launch window contains a button corresponding to each statistical and graphical procedure in the system. As you mouse over each button, a brief
paragraph explaining the main purpose of the currently selected procedure will appear in the message box to the right. The Quick Launch makes it easy to find and launch any procedure from a single screen.
New Features:
Enhanced User Interface
The procedure interfaces have been redesigned to make the user input easier to
complete. Boxes containing descriptive titles have been added to group similar options together. This allows for easier navigation of the procedure windows and faster identification of input categories.
Improved Help System
The NCSS Help System has been improved in NCSS 2007 to make it easier to find the topic you are looking for.
It is also now easier than ever to print help topics. The new help system consolidates the PDF documentation and the Help System. Adobe Reader Version 7 or later is required to use the new NCSS Help System. You can download the latest version of Adobe Reader by clicking on the link below. The new help system is fully compatible with Windows
Vista.
PASS Home
PASS is easy to navigate with a simple procedure selection window. Simply scroll down the list and expand the tree to find the procedure you want. A message on the right gives an explanation of each procedure.
Procedure Window
Once you select a procedure from the tree or menus, the corresponding
Procedure Window appears. This window lets you quickly and easily specify the power analysis or sample size parameters. The immediate help window on the right gives you a brief explanation of each option as the mouse passes over it. You can save the settings in a template file for future use.
Output
All reports are displayed using our builtin
Word Processor. You can quickly view, edit, save, and print your output. Reports are stored in the generic RTF (rich text) format that can be read by most word processors, so you can easily save PASS reports for further use in Word or WordPerfect. The output document mixes text and graphs together. The text portions of the reports are
formatted using tabs (not spaces), so they are easily reformatted.
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