The RELIABILITY Procedure
- Overview
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Getting Started
Analysis of Right-Censored Data from a Single PopulationWeibull Analysis Comparing Groups of DataAnalysis of Accelerated Life Test DataWeibull Analysis of Interval Data with Common Inspection ScheduleLognormal Analysis with Arbitrary CensoringRegression ModelingRegression Model with Nonconstant ScaleRegression Model with Two Independent VariablesWeibull Probability Plot for Two Combined Failure ModesAnalysis of Recurrence Data on RepairsComparison of Two Samples of Repair DataAnalysis of Interval Age Recurrence DataAnalysis of Binomial DataThree-Parameter WeibullParametric Model for Recurrent Events DataParametric Model for Interval Recurrent Events Data -
SyntaxPrimary StatementsSecondary StatementsGraphical Enhancement StatementsPROC RELIABILITY StatementANALYZE StatementBY StatementCLASS StatementDISTRIBUTION StatementEFFECTPLOT StatementESTIMATE StatementFMODE StatementFREQ StatementINSET StatementLOGSCALE StatementLSMEANS StatementLSMESTIMATE StatementMAKE StatementMCFPLOT StatementMODEL StatementNENTER StatementNLOPTIONS StatementPROBPLOT StatementRELATIONPLOT StatementSLICE StatementSTORE StatementTEST StatementUNITID Statement
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DetailsAbbreviations and NotationTypes of Lifetime DataProbability DistributionsProbability PlottingNonparametric Confidence Intervals for Cumulative Failure ProbabilitiesParameter Estimation and Confidence IntervalsRegression Model Statistics Computed for Each Observation for Lifetime DataRegression Model Statistics Computed for Each Observation for Recurrent Events DataRecurrence Data from Repairable SystemsODS Table NamesODS Graphics
- References
This section describes various types of data that you can analyze with the RELIABILITY procedure.
Lifetime data for which the values of all sample units are observed are called complete data. This means that the failure times are observed for all units.
Many practical problems in life data analysis involve data for which some units are unfailed. The failure time for an unfailed unit is known only to be greater than the last running time. This type of data is said to be right censored, and the censoring time is used in the analysis of the data. Data for which censoring times are intermixed with failure times are sometimes called multiply censored or progressively censored.
Failure times may be known only to be less than some value. This type of data is called left censored.
Another common situation is where the failure times of units are not known exactly, but time intervals that contain the failure times are known. This type of data is called interval censored.
Interval-censored data for which all units share common interval endpoints are called readout, inspection, or grouped data.
Arbitrarily censored data can contain a combination of failures, right-, left-, and interval-censored data.