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Mplus版本8現已推出。
新功能：
時間序列分析功能
N = 1次時間序列分析
兩級時間序列分析
交叉分類時間序列分析
時間序列圖
其他新功能
隨機差異的兩級建模
兩級隨機自相關建模
具有隨機斜率和隨機方差的兩級模型的標準化
具有缺失數據的協變量的隨機斜率
兩級模型的散點圖和直方圖之間的新內部，包括樣本和模型估計的特定於簇的方法和方差
BSEM的新的後期預測性P值
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 Mplus
Version 8 is available for Windows, Mac OS X,
and Linux for both 32- and
64-bit computers. In Version 8, the Mac OS X version is available
using a new editor in addition to the command line. Two minor
additions have also been made to accommodate the analyses in the
Muthen (2011) paper Applications of causally defined direct and
indirect effects in mediation analysis using SEM in Mplus. A normal
distribution function (PHI) has been added to the DEFINE and MODEL
CONSTRAINT commands and the FREQWEIGHT option is now available with
ESTIMATOR=BAYES.
Mplus is a statistical modeling program that provides researchers
with a flexible tool to analyze their data. Mplus offers researchers
a wide choice of models, estimators, and algorithms in a program
that has an easy-to-use interface and graphical displays of data and
analysis results. Mplus allows the analysis of both cross-sectional
and longitudinal data, single-level and multilevel data, data that
come from different populations with either observed or unobserved
heterogeneity, and data that contain missing values. Analyses can be
carried out for observed variables that are continuous, censored,
binary, ordered categorical (ordinal), unordered categorical
(nominal), counts, or combinations of these variable types. In
addition, Mplus has extensive capabilities for Monte Carlo
simulation studies, where data can be generated and analyzed
according to any of the models included in the program.
Mplus is a latent variable
modeling program with a wide variety of analysis capabilities:
˙Exploratory
factor analysis
˙Structural
equation modeling
˙Item
response theory analysis
˙Growth
modeling
˙Mixture
modeling (latent class analysis)
˙Longitudinal
mixture modeling (hidden Markov, latent transition
analysis, latent class growth analysis, growth mixture
analysis)
˙Survival
analysis (continuous- and discrete-time)
˙Multilevel
analysis
˙Complex
survey data analysis
˙Bayesian
analysis
˙Monte
Carlo simulation
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