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1. MindManager 視覺化思考繪圖軟體
2. EViews 預測分析計量軟體
3. LISREL 線性結構分析軟體

4.

ATLAS.ti 定性量化分析軟體
5.

EndNote 參考書目軟體

6.

Stata 資料管理統計繪圖軟體

7. See5/C5.0  資料探勘軟體
8. HLM 階層分析軟體
9.

Expert Choice  AHP專家決策分析軟體

10. Grapher 3D科學繪圖軟體

 

 

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SuperMix     混合模型分析軟體


 

SuperMix是由DonaldHedeker教授和RobertGibbons教授以及SSI共同開發的處理混合模型又稱階層模型的軟體。該軟體可以對二層和三層資料進行線性處理。SuperMix適用於對連續(continuous)因變數、二元(binary)因變數、計數(count)因變數、順序(ordinary)因變數和名義因變數進行模型分析。這一類分析被廣泛應用於社會學、醫藥領域、經濟學、工商業等各個領域。
該軟體的人性化設計給用戶提供了如下功能:
簡單直觀的視窗使複雜的模型設計變得簡便易行。
允許連續因變數(continuous outcome)混合模型中,因變數有自相關殘差(auto-correlated residuals)。
在順序因變數混合模型中可以包含scaling effects並進行non-proportional odds模型分析。
進行泊松分佈混合模型分析。
名義因變數的 logistic regression模型分析。
分組時間序列的grouped-time survival混合模型分析。
二層和三層混合模型分析。
直觀的圖表。

SuperMix combines the functionality of four mixed-effects programs, MIXREG, MIXOR, MIXNO, and MIXPREG, developed by Donald Hedeker and Robert Gibbons into a single application to provide estimates for mixed-effects regression models.

Mixed-effects models are also known as multilevel, hierarchical, or random-effects models. These models can be used for the analysis of longitudinal data, where each individual may be measured at a different number of occasions. They can also be used for clustered data, such as for patients within clinics.

SuperMix has been developed by SSI under an SBIR Phase II contract N44MH32056, and has been released in September 2008. SuperMix will fit models with continuous, count, ordinal, nominal, and survival outcome variables with nested data, allowing for up to three levels of nesting. Key features are listed below.

Easy to use graphical user interface: import data into the SuperMix spreadsheet, then build new models using menus and dialog boxes.
Mixed-effects models for continuous outcome variables with auto-correlated residuals.
Mixed-effects models for ordinal regression analysis, including non-proportional odds models and scaling effects.
Mixed-effects models for Poisson regression analysis.
Mixed-effects models for nominal logistic regression analysis.
Mixed-effects models for grouped-time survival analysis.
Two- and three-level models allowing for nested designs.
Presentation quality graphics.

 

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