逐步回歸分析
And multi-element stepwise regression analysis showed the influencing factors included smoking, source of medical costs, culture level and age.
多元逐步回歸分析顯示，吸煙、醫療費用來源、文化程度、年齡是影響因素。
Stepwise regression analysis revealed that total social support, anxiety of study, grade, loss and sex were significant predictors of positive coping style.
多元逐步回歸分析顯示：以積極應對方式為因變量，進入方程的變量依次有：社會支持總計、學習焦慮、年級、喪失、性别。
Univariate and multivariate stepwise regression analysis were performed to assess the factors related to QOL with the total scores as dependent variables, and screen the main factors.
将總評分作為因變量，對影響生活質量的因素進行單因素分析和多因素逐步回歸分析，篩選主要影響因素。
According to the correla s tion and stepwise regression analysis, it was suggested that the ears Pernu and grains Per ear Were the main objectives for high yield cultivation.
根據相關和逐步回歸分析，确立了畝穗數、穗粒數為相應品種類型的高産栽培主攻目标。
In this study, through stepwise regression analysis, the factors influencing the economic burden are selected, which are the hospital days , place of diagnosis, number of visits, etc.
本研究采用逐步回歸分析方法，對瘧疾病例經濟負擔的影響因素進行了分析。
MethodsThe potential factors which may cause PCO were analyzed with multiple stepwise regression analysis.
方法采用多元逐步回歸方法對可能引起後囊膜混濁的諸多因素進行分析。
The t-test and stepwise regression analysis were performed in both groups to determine the correlated factors of gummy smile deformity.
采用t檢驗及回歸分析比較兩組患者各參數的差異，并分析與微笑露龈畸形相關的因素。
The single factor correlation analysis and multiple stepwise regression analysis showed that the intelligent development index increased with the increase of family income;
單因素相關分析和多元逐步回歸分析顯示，智力發展指數隨着家庭經濟收入的增高而增高；
The multi-factor stepwise regression analysis indicated that there was linear between the uric acid with the tubular score, BMI, triglyceride and Mean arterial pressure.
③多元線性逐步回歸分析表明，腎小管間質積分、體重指數、甘油三酯、平均動脈壓是血尿酸獨立危險因素。
The correlation between changes of AF in surgical area and visual function were analyzed by multiple linear stepwise regression analysis.
對比周邊視野檢查結果，對手術區AF變化與視功能改變進行多元線性逐步回歸分析。
A linear stepwise regression analysis indicated that serum MIC-1 was independently associated with age, FPG and gender.
多元線性逐步回歸分析提示年齡、空腹血糖、性别均與血清MIC-1獨立相關。
By using the methods of grey relational analysis, stepwise regression analysis and key part analysis find the key factors.
然後分别運用灰度關聯、逐步回歸分析、主成分方法選取主要影響因素；
By using the methods of grey relational analysis, stepwise regression analysis and key part analysis the key factors are fownd.
然後分别運用灰度關聯、逐步回歸分析、主成分方法選取主要影響因素；
Multiple stepwise regression analysis showed that the AD1, systolic pressure, EF, MPAD, history of drinking, SV, sex and RAD were independent parameters to LVMI.
LVMI影響因素的逐步回歸分析提示主動脈舒張内徑、收縮壓、EF、MPAD、飲酒史、左室每搏量（SV）、性别、右房橫徑（RAD）是LVMI的影響因素，并建立回歸方程。
The data was analyzed by chi-square, stepwise regression analysis and covariance statistics.
資料用卡方檢驗、逐步回歸和協方差分析等。
By applying mathematical statistics and stepwise regression analysis, regression models are established, and regression assumptions are verified.
應用數理統計和逐步回歸原理，建立了最大收縮長度和影響參數的數學模型，并進行了模型的檢驗；
It was found that main predicting factors for level of stress and response to stress varied in managers and clerks with stepwise regression analysis.
管理人員緊張反應與緊張水平的強預測因素與營業員有所差異。
The stepwise regression analysis approach, which is used to classify the wear model of Ferrous metal in ship ***sel , is discussed.
探讨了将逐步回歸分析方法用于船舶柴油機黑色金屬磨損狀态分類模型的方法和技術。
Stepwise regression analysis showed that insulin and peptide C were independently correlated with the severity of coronary lesions.
逐步回歸分析顯示血清胰島素和C肽與冠狀動脈病變程度獨立相關。
Then, stepwise regression analysis is used to select a best group of factors for the prediction of expressway incident duration, and the multiple linear regression model is established.
在此基礎上，通過逐步回歸分析确定用于高速公路事件持續時間預測的最佳變量組合并建立多元線性回歸模型。
By stepwise regression analysis of test results, the notabilities of effect on stress corrosion cracking susceptive indexes of medium parameters are revealed.
通過試驗數據的逐步回歸分析，進一步揭示試驗介質參數對應力腐蝕敏感性指數影響的顯著性。
Multiple stepwise regression analysis showed that the number of complications, monthly income, age, and T stage were independent factors affecting total QOL.
多重逐步回歸分析結果表明，并發病數目、月收入、年齡和T分期是影響患者總的生存質量的獨立因素。
Multivariant linear stepwise regression analysis show that the pulse pressure, the systolic pressure , overdose compliance are important influencing factors of IMT.
多元線性逐步回歸分析顯示脈壓、收縮壓、服藥依從性是IMT的重要影響因素。
Methods To analyse 3 765 cases of schizophrenia in hospital from 1995 to 1997 with the t-test, analysis of variance and stepwise regression analysis by SPSS software.
方法應用SPSS統計軟件對1995-1997年内住院的3765例精神分裂症病人進行方差分析和逐步回歸分析。
逐步回歸分析（Stepwise Regression Analysis）是一種統計學中常用的變量選擇方法，其核心目标是通過自動化的步驟篩選出對因變量解釋力最強的自變量組合，從而構建最優的線性回歸模型。該方法結合了向前選擇法（Forward Selection）和向後剔除法（Backward Elimination），通過不斷添加或删除變量來評估模型的解釋能力。
向前選擇法
從零變量開始，逐步将統計顯著性最高的自變量加入模型，直至新增變量無法顯著提升模型拟合度（通常以p值<0.05為阈值）。
向後剔除法
從包含全部自變量的模型開始，逐步移除統計顯著性最低的變量，直至剩餘變量均滿足顯著性要求。
雙向逐步回歸
綜合前兩種方法，在每一步同時考慮添加或删除變量，以平衡模型的簡潔性與預測能力。
該方法常用于醫學研究、經濟學和社會科學領域，例如分析疾病風險因素或經濟指标相關性。然而，其局限性包括：
通過合理應用逐步回歸分析，研究者可在控制模型複雜度的同時，有效識别關鍵影響因素，但需結合領域知識驗證結果的現實意義。
逐步回歸分析（Stepwise Regression Analysis）是一種統計建模方法，用于從多個候選自變量中篩選出對因變量有顯著影響的變量，最終構建一個簡潔且有效的回歸模型。其核心特點是“逐步”選擇變量，每一步都可能添加或移除變量，具體分為以下三種常見類型：
前向選擇（Forward Selection）
從零變量模型開始，每一步将統計顯著性最強（如p值最小）的自變量加入模型，直到沒有符合預設阈值（如p值<0.05）的變量可加入。
後向消除（Backward Elimination）
從包含所有自變量的模型開始，逐步移除統計顯著性最弱的變量（如p值>0.10），直到所有剩餘變量均顯著。
逐步回歸（Stepwise Regression）
結合前向和後向策略，每一步在添加新變量後重新評估已有變量，移除可能因新變量加入而變得不顯著的變量。
如果需要具體案例或操作步驟，可進一步說明應用場景或工具（如R、Python中的實現方法）。
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