Glossary of Terms in English and Traditional Chinese (中英術語對照)
In this appendixhow the glossary was compiled and how to use it; the glossary of 548 terms with their Traditional Chinese equivalents and the chapters in which they are used.
This appendix lists the key terms of the book with their equivalents in Traditional Chinese, as they are used in the methodological literature of psychology, education, and the social sciences in Taiwan. It is meant for readers who study with Chinese-language textbooks alongside this book, who write theses or articles in Chinese, or who teach multilevel modeling in Chinese. The glossary is not a dictionary: it gives the rendering that a reader is most likely to meet, lists other renderings in common use, and points to the chapters where each term is used.
F.1Using the Glossary#
The glossary in Section F.2 lists 548 terms in alphabetical order of the English term. For each term it gives the Traditional Chinese equivalent, other renderings in common use (for 223 terms), and three chapter numbers: the first chapter that defines the term as a key term, printing it in bold or listing it among the chapter’s key terms (Key, for 432 terms), the chapter in which it first occurs (First), and the chapter in which it occurs most often (Main). The chapters mark 618 distinct key terms, in bold or in their lists of key terms. Of these, 526 have an entry of their own, 74 are covered by a shorter or broader entry (for example, “class contextual effect” under “contextual effect”), and 18 are not covered: parts of longer terms (such as “atomistic” and “fallacy”), single words used in a narrower sense in one chapter (such as “marginal” and “conditional”), phrases used in only one chapter (such as “three-part decomposition” and “weighted combination of slopes”), and names of data sets. The three chapter columns were not assigned by hand, apart from two Key entries set after checking: a script searched the running text of the 37 chapters and appendices (Chapters 1 to 32 and Appendices A to E) for each term, its inflected forms, and its abbreviation (except HLM, which also names a program), recorded the first chapter with a match and the chapter with the most matches, and matched each term against the key terms of every chapter. Because Chapter 1 previews the whole book, 85 terms occur first there, often in a single sentence; the Key and Main columns are then the better guides to the chapter that treats the term in depth. The search counts every occurrence of the words, including occurrences in a different sense, so the columns are a guide rather than an index.
The renderings follow a few conventions. “Effect” is rendered 效果 (固定效果, 隨機效果, 脈絡效果), the usual form in Taiwan; established names such as 大魚小池效應 keep 效應. “Model” is rendered 模型; the form 模式 remains common in Taiwanese theses and textbooks and is the more frequent form in 階層線性模式 and 結構方程模式; it is the primary rendering here for the hierarchical linear model, which the psychology and education glossaries of the National Academy for Educational Research give only as 階層線性模式, and an alternative for the multilevel model and the structural equation model. “Centering” is 平減, the form used in the Taiwanese multilevel literature, with 總平減 for grand-mean centering and 組平減 for group-mean centering; 中心化 is also understood. “Level” is 層次; the glossary renders level-1 and level-2 as 第一層 and 第二層 and lists 層次一 and 層次二 as other renderings. “Variable” is 變項 in psychology and education and 變數 in statistics and economics; the glossary uses 變項 (潛在變項, 虛擬變項) and renders “covariate” as 共變項, because 共變數 means covariance. Abbreviations such as REML, ICC, MCMC, and AIC are usually kept in Latin letters in Chinese texts. Names of persons are also usually left in Latin letters (Satterthwaite, Kenward–Roger, Wald, Cholesky, Kronecker, Hausman), except where an established transliteration exists (費雪, 拉普拉斯, 卜瓦松, 馬可夫). Because renderings vary, a thesis or article in Chinese should give the English term, and its abbreviation, in parentheses when a technical term is first used, for example 組內相關係數(intraclass correlation coefficient, ICC). Readers who need the official rendering of a term in a particular discipline can consult the terminology database of the National Academy for Educational Research (樂詞網, https://terms.naer.edu.tw).
F.2The Glossary#
The glossary follows in Table F.1. Terms whose English form includes an abbreviation are sorted by the full term; the abbreviation is given in parentheses. Terms that the book introduces itself, such as the Unified Model Graph (Chapter 2 and Appendix D), its plates and mixing edges, parameter promotion, and causal badges, have no established Chinese rendering; the renderings given for them (統一模型圖, 板塊, 混合邊, 參數提升, 因果標記) are proposals.
| English | Traditional Chinese | Other renderings | Key | First | Main |
|---|---|---|---|---|---|
| A | |||||
| accuracy-bias trade-off | 準確度與偏誤的權衡 | 偏誤-準確度權衡 | 7 | 7 | 7 |
| actor effect and partner effect | 行動者效果與伴侶效果 | 27 | 27 | 27 | |
| actor-partner interdependence model | 行動者-伴侶相依模型 | 行動者與伴侶相依模式;行動者與夥伴相互依賴模式 | 27 | 27 | 27 |
| adaptive Gauss–Hermite quadrature | 適應性高斯積分法 | 適應性高斯求積法 | 23 | 23 | 23 |
| adjacent-category logit | 相鄰類別勝算對數 | 相鄰類別邏輯模型 | 24 | 24 | 24 |
| adjustment set | 調整集合 | 調整變項集合 | 31 | 12 | 31 |
| aggregation | 聚合 | 資料聚合 | 1 | 1 | 30 |
| Akaike information criterion (AIC) | 赤池訊息準則 | – | 5 | 11 | |
| analysis of covariance (ANCOVA) | 共變數分析 | 3 | 3 | 5 | |
| analysis of variance (ANOVA) | 變異數分析 | – | 1 | 3 | |
| atomistic fallacy | 原子謬誤 | 原子論式謬誤;個體謬誤 | 1 | 1 | 1 |
| attenuation factor | 衰減因子 | 23 | 23 | 23 | |
| attrition | 樣本流失 | – | 16 | 16 | |
| autocorrelation | 自我相關 | 自相關 | – | 4 | 20 |
| autoregressive effect (inertia) | 自我迴歸效果(慣性) | 21 | 21 | 21 | |
| autoregressive moving average (ARMA) | 自我迴歸移動平均 | 20 | 20 | 20 | |
| autoregressive structure, AR(1) | 一階自我迴歸結構 | – | 20 | 20 | |
| auxiliary variable | 輔助變項 | 17 | 17 | 17 | |
| B | |||||
| back-door path | 後門路徑 | 31 | 31 | 31 | |
| balanced design | 平衡設計 | – | 1 | 26 | |
| baseline-category logit | 基準類別勝算對數 | 基線類別邏輯模型 | 24 | 24 | 24 |
| baseline hazard | 基準風險 | 基線風險 | 25 | 25 | 25 |
| Bayes factor | 貝氏因子 | – | 13 | 13 | |
| Bayesian estimation | 貝氏估計 | – | 1 | 13 | |
| Bayesian information criterion (BIC) | 貝氏訊息準則 | – | 11 | 11 | |
| Bernoulli distribution | 伯努利分配 | 柏努利分配 | 23 | 4 | 23 |
| best linear unbiased predictor (BLUP) | 最佳線性不偏預測值 | 12 | 5 | 12 | |
| between-cluster effect (between slope) | 組間效果 | 群間效果 | 7 | 1 | 7 |
| between-cluster regression | 組間迴歸 | 3 | 3 | 3 | |
| between-person differences | 個人間差異 | 28 | 1 | 21 | |
| bias | 偏誤 | 偏差 | – | 1 | 21 |
| big-fish-little-pond effect | 大魚小池效應 | 7 | 7 | 7 | |
| binary outcome | 二元結果變項 | 二分變項 | – | 1 | 23 |
| binomial distribution | 二項分配 | 23 | 23 | 23 | |
| blended analysis | 融合分析 | 32 | 32 | 32 | |
| bootstrap | 拔靴法 | – | 10 | 10 | |
| boundary estimate | 邊界估計值 | 9 | 4 | 11 | |
| boundary of the parameter space | 參數空間邊界 | 11 | 4 | 9 | |
| burn-in (warmup) | 暖身期 | 預燒期 | 13 | 13 | 13 |
| C | |||||
| caterpillar plot (display) | 毛毛蟲圖 | 4 | 4 | 4 | |
| causal badge | 因果標記 | 31 | 31 | 31 | |
| causal inference | 因果推論 | – | 31 | 31 | |
| cause-specific hazard | 原因別風險函數 | 特定原因風險 | 25 | 25 | 25 |
| censoring | 設限 | 截尾 | 25 | 13 | 25 |
| centering | 平減 | 中心化;置中 | – | 1 | 7 |
| chi-square distribution | 卡方分配 | 卡方分布 | – | 7 | A |
| chi-square mixture | 卡方混合分配 | 混合卡方分配 | 11 | 6 | A |
| Cholesky decomposition | Cholesky 分解 | 喬列斯基分解;柯列斯基分解 | – | 13 | 15 |
| class enumeration | 類別數目決定 | 潛在類別數的決定 | 22 | 22 | 22 |
| classification diagram | 分類圖 | 26 | 26 | 26 | |
| cluster | 叢集 | 群集;集群 | – | 1 | 31 |
| cluster bias | 叢集偏誤 | 30 | 30 | 30 | |
| cluster confounding | 叢集層次混淆 | 叢集混淆 | 31 | 7 | 31 |
| cluster mean | 組平均數 | 群體平均數 | 4 | 1 | 7 |
| cluster-randomized trial | 集群隨機試驗 | 群集隨機化試驗 | 1 | 1 | 16 |
| cluster-robust standard error | 叢集穩健標準誤 | 3 | 3 | 32 | |
| cluster size | 叢集大小 | 群集規模 | – | 1 | 16 |
| clustered data | 叢集資料 | 群聚資料 | – | 3 | 31 |
| common-effect model | 共同效果模型 | 27 | 27 | 27 | |
| comparative and diagnostic standard errors | 比較用與診斷用標準誤 | 12 | 12 | 12 | |
| competing risks | 競爭風險 | 互競風險 | 25 | 25 | 25 |
| complete pooling | 完全合併 | 3 | 3 | 3 | |
| complex sample (complex sampling design) | 複雜樣本(複雜抽樣設計) | 複雜抽樣;複合抽樣設計 | 17 | 17 | 17 |
| composition model | 組合模型 | 組成模型 | 30 | 30 | 30 |
| compositional effect | 組成效果 | – | 3 | 7 | |
| compound symmetry | 複合對稱 | 2 | 2 | 19 | |
| conditional AIC | 條件 AIC | 條件赤池訊息準則 | 11 | 11 | 11 |
| conditional (level-1) residual | 條件殘差(第一層殘差) | 層次一殘差 | 14 | 2 | 15 |
| conditional level-1 weight | 條件第一層權數 | 條件層次一權數 | 17 | 17 | 17 |
| conditional model | 條件模型 | – | 24 | 24 | |
| confidence interval | 信賴區間 | – | 1 | 27 | |
| confirmatory factor analysis (CFA) | 驗證性因素分析 | – | 22 | 22 | |
| conflated effect (conflation of levels) | 混同效果 | 29 | 29 | 29 | |
| conflated random slope | 混同隨機斜率 | 混淆隨機斜率 | 7 | 6 | 14 |
| confounded residuals | 混淆殘差 | 15 | 15 | 15 | |
| confounding (confounder) | 混淆(混淆變項) | 混雜 | – | 3 | 31 |
| congeniality | 契合性 | 相容性 | 17 | 17 | 17 |
| containment and between-within degrees of freedom | 包含法與組間-組內自由度 | 10 | 10 | 10 | |
| contextual effect | 脈絡效果 | 情境效果 | 5 | 3 | 7 |
| continuation-ratio model | 延續比模型 | 連續比模型 | 24 | 24 | 24 |
| continuous-time AR(1) | 連續時間一階自我迴歸 | 20 | 20 | 20 | |
| contrast coding | 對比編碼 | – | E | E | |
| contrast matrix | 對比矩陣 | 10 | 10 | 10 | |
| convergence | 收斂 | – | 7 | 9 | |
| Cook’s distance | Cook 距離 | 15 | 15 | 15 | |
| correlation map | 相關矩陣圖 | 相關圖 | 4 | 4 | 4 |
| count outcome | 計數結果變項 | 計次資料 | – | 1 | 24 |
| counting process | 計數過程 | 25 | 25 | 25 | |
| covariance matrix of the random effects | 隨機效果共變數矩陣 | 2 | 2 | 22 | |
| covariance structure | 共變數結構 | – | 2 | 20 | |
| covariate | 共變項 | 共變量 | – | 4 | 28 |
| coverage (of an interval) | 涵蓋率 | 覆蓋率 | – | 3 | 24 |
| Cox proportional hazards model | Cox 比例風險模型 | 25 | 25 | 25 | |
| CR2 (bias-reduced linearization) | CR2(偏誤縮減線性化) | 10 | 10 | 15 | |
| credible interval | 可信區間 | 13 | 13 | 13 | |
| cross-classified model | 交叉分類模型 | 1 | 1 | 26 | |
| cross-lagged panel model | 交叉延宕模型 | 長期追蹤交叉延宕模式;交叉延宕模式 | 21 | 21 | 21 |
| cross-level interaction | 跨層級交互作用 | 跨層次交互作用 | 1 | 1 | 6 |
| cross-level invariance | 跨層級不變性 | 跨層次不變性;跨層次測量恆等性 | 29 | 29 | 30 |
| cross-sectional data | 橫斷面資料 | – | 4 | 19 | |
| cross-site variance of the effect | 效果之跨地點變異 | 31 | 16 | 31 | |
| cross-validation | 交叉驗證 | 交叉效化 | – | 13 | 32 |
| crossed random effects | 交叉隨機效果 | 26 | 1 | 26 | |
| cumulative incidence | 累積發生率 | 25 | 25 | 25 | |
| cumulative logit model | 累積勝算對數模型 | 累積邏輯模型 | 24 | 24 | 24 |
| D | |||||
| data audit | 資料稽核 | 4 | 4 | 4 | |
| definition variable | 定義變項 | 22 | 22 | 22 | |
| degrees of freedom | 自由度 | – | 1 | 10 | |
| delta adjustment | Delta 調整 | 17 | 17 | 17 | |
| delta method | Delta 法 | – | 10 | A | |
| design-based inference | 設計基礎推論 | 循設計推論 | 17 | 7 | 17 |
| design effect | 設計效果 | 1 | 1 | 1 | |
| design matrix | 設計矩陣 | 2 | 2 | 26 | |
| detrending | 去趨勢 | 21 | 19 | 21 | |
| deviance | 離異數 | 離差量數 | – | 2 | 9 |
| diagnostics | 模型診斷 | 診斷 | – | 1 | 15 |
| difference-in-differences | 差異中之差異 | 31 | 31 | 31 | |
| differential item functioning (DIF) | 差異試題功能 | 30 | 30 | 30 | |
| direct effect | 直接效果 | 29 | 21 | 29 | |
| directed acyclic graph (DAG) | 有向無環圖 | – | 31 | 31 | |
| disaggregation | 解聚 | 解構;分解 | 1 | 1 | 1 |
| discrete-time survival (hazard) model | 離散時間存活模型 | 25 | 25 | 25 | |
| distal outcome | 遠端結果 | 22 | 22 | 22 | |
| distinguishable dyads | 可區辨對偶 | 27 | 27 | 27 | |
| distributional regression | 分配迴歸 | 28 | 28 | 28 | |
| divergent transitions | 發散轉移 | 13 | 13 | 13 | |
| doubly latent model | 雙重潛在模型 | 29 | 7 | 29 | |
| dropout | 中途退出 | 樣本流失 | 19 | 17 | 25 |
| dummy variable | 虛擬變項 | – | 1 | 3 | |
| dyadic data | 對偶資料 | 二人組資料 | 27 | 11 | 27 |
| dynamic structural equation model (DSEM) | 動態結構方程模型 | 21 | 13 | 21 | |
| E | |||||
| ecological fallacy | 生態謬誤 | 1 | 1 | 1 | |
| ecological momentary assessment (EMA) | 生態瞬時評估 | 生態瞬間評估法 | – | 21 | 21 |
| effect size | 效果量 | – | 1 | 27 | |
| effective degrees of freedom | 有效自由度 | 32 | 11 | 32 | |
| effective sample size (ESS) | 有效樣本數 | 1 | 1 | 13 | |
| eigenvalue | 特徵值 | – | 9 | A | |
| empirical Bayes estimate | 經驗貝氏估計值 | 12 | 3 | 12 | |
| empty (null) model | 虛無模型 | 空模型;零模型 | 1 | 1 | 5 |
| endogeneity | 內生性 | – | 32 | 32 | |
| entropy | 熵 | 分類熵 | 22 | 22 | 22 |
| equivalent models | 等價模型 | 等值模型 | 7 | 5 | 7 |
| error contrast | 誤差對比 | 9 | 9 | 9 | |
| estimated marginal means | 估計邊際平均數 | 10 | 10 | 10 | |
| estimator | 估計式 | 估計量 | – | 1 | 31 |
| event history analysis | 事件史分析 | 25 | 25 | 25 | |
| exact restricted likelihood-ratio test | 精確限制概似比檢定 | 11 | 11 | 11 | |
| exchangeability | 可交換性 | – | 4 | 32 | |
| expectation-maximization (EM) algorithm | 期望最大化演算法 | EM 演算法 | 9 | 9 | 9 |
| expected log predictive density (ELPD) | 期望對數預測密度 | 13 | 13 | 13 | |
| experience sampling method (ESM) | 經驗取樣法 | – | 20 | 21 | |
| explanatory item response model | 解釋性試題反應模型 | 30 | 30 | 30 | |
| exposure | 暴露量 | 24 | 24 | 24 | |
| F | |||||
| factor intraclass correlation | 因素組內相關 | 因素的組內相關係數 | 29 | 29 | 30 |
| factor loading | 因素負荷量 | – | 22 | 22 | |
| family-wise error rate | 族系錯誤率 | 家族錯誤率;族系誤差率 | 10 | 10 | 10 |
| fan of cluster lines | 叢集迴歸線的扇形分布 | 6 | 2 | 6 | |
| final-model table | 最終模型表 | 18 | 18 | 18 | |
| Fisher scoring | 費雪計分法 | 9 | 9 | 9 | |
| fixed effect | 固定效果 | 固定效應 | 2 | 1 | 10 |
| fixed-effects regression (econometric fixed-effects model) | 固定效果模型 | 3 | 3 | 7 | |
| fixed part and random part | 固定部分與隨機部分 | 2 | 2 | 14 | |
| fixed versus random clusters | 固定叢集與隨機叢集 | 3 | 3 | 3 | |
| fraction of missing information | 遺漏訊息比例 | 17 | 13 | 17 | |
| frailty | 脆弱性 | 脆弱因子 | 25 | 25 | 25 |
| full information maximum likelihood (FIML) | 完整訊息最大概似估計 | 全訊息最大概似估計 | 17 | 17 | 22 |
| fully and partially crossed designs | 完全交叉與部分交叉設計 | 26 | 26 | 26 | |
| fully conditional specification | 完全條件設定 | 完整條件規範;鏈式方程插補 | 17 | 17 | 17 |
| funnel plot | 漏斗圖 | 15 | 15 | 15 | |
| G | |||||
| generalized additive mixed model (GAMM) | 廣義加成混合模型 | 32 | 32 | 32 | |
| generalized estimating equations (GEE) | 廣義估計方程式 | 廣義估計方程 | 23 | 2 | 32 |
| generalized least squares (GLS) | 廣義最小平方法 | 9 | 5 | 9 | |
| generalized linear mixed model (GLMM) | 廣義線性混合模型 | 1 | 1 | 24 | |
| Gibbs sampler | Gibbs 抽樣法 | 吉布斯抽樣 | 13 | 13 | 13 |
| GLMM tree | GLMM 樹 | 廣義線性混合模型樹 | 32 | 32 | 32 |
| grand-mean centering | 總平減 | 總平均數平減;總平均數中心化 | 4 | 4 | 7 |
| group-based trajectory model | 群組基礎軌跡模型 | 組別軌跡模型 | 22 | 22 | 22 |
| group-mean centering (centering within clusters) | 組平減 | 組平均數平減;組平均數中心化 | 4 | 4 | 7 |
| growth curve model | 成長曲線模型 | 成長模型 | – | 1 | 19 |
| growth factor | 成長因素 | 成長因子 | 22 | 19 | 22 |
| growth mixture model | 成長混合模型 | 22 | 2 | 22 | |
| growth trajectory | 成長軌跡 | – | 4 | 19 | |
| H | |||||
| half- and half-Cauchy priors | 半 t 與半柯西先驗分配 | 13 | 13 | 13 | |
| Hamiltonian Monte Carlo (HMC) | 漢米爾頓蒙地卡羅法 | 13 | 13 | 13 | |
| harmonic mean cluster size | 調和平均叢集大小 | 叢集大小的調和平均數 | 11 | 5 | 11 |
| Hausman test | Hausman 檢定 | 豪斯曼檢定 | 7 | 7 | 7 |
| hazard | 風險函數 | 危險函數 | 25 | 25 | 25 |
| Hessian matrix | 海森矩陣 | – | 9 | 24 | |
| heterogeneity | 異質性 | 27 | 1 | 27 | |
| heterogeneity model | 異質性模型 | 常態混合隨機效果模型 | 12 | 12 | 12 |
| heterogeneous variance | 異質變異數 | 20 | 13 | 20 | |
| heteroscedasticity | 變異數異質性 | 6 | 2 | 15 | |
| Heywood case | Heywood 案例 | 不適當解 | 22 | 22 | 22 |
| hierarchical linear model (HLM) | 階層線性模式 | 階層線性模型 | 1 | 1 | 1 |
| hierarchical view (level-specific view) | 階層觀點 | 層次別觀點 | 2 | 2 | 2 |
| Holm adjustment | Holm 校正 | Holm 調整法 | 10 | 10 | 10 |
| homogeneity chi-square test (homogeneity statistic) | 同質性卡方檢定(同質性統計量) | 同質性檢定;均齊性檢定 | 11 | 11 | 14 |
| homoscedasticity | 變異數同質性 | – | 24 | 24 | |
| hurdle model | 障礙模型 | 柵欄模型;跨欄模型 | 24 | 24 | 24 |
| I | |||||
| identification | 識別 | 辨識 | – | 22 | 31 |
| ignorable missingness | 可忽略遺漏 | 17 | 17 | 17 | |
| ignoring a level | 忽略一個層次 | 忽略某一層次 | 8 | 8 | 8 |
| imputation | 插補 | 設算 | – | 17 | 17 |
| imputation model and analysis model | 插補模型與分析模型 | 17 | 16 | 17 | |
| indirect effect | 間接效果 | 29 | 29 | 29 | |
| influence (diagnostics) | 影響力 | – | 15 | 15 | |
| information criterion | 訊息準則 | 資訊準則 | 11 | 5 | 11 |
| information matrix | 訊息矩陣 | – | 9 | 11 | |
| informative sampling design | 具訊息的抽樣設計 | 17 | 17 | 17 | |
| initial status | 起始狀態 | 初始狀態 | 19 | 19 | 19 |
| innovation (time series) | 新息 | 創新項 | 21 | 20 | 21 |
| intensive longitudinal data | 密集縱貫資料 | 21 | 13 | 21 | |
| interaction | 交互作用 | – | 1 | 6 | |
| intercept–slope covariance | 截距-斜率共變數 | 截距與斜率的共變數 | 6 | 2 | 6 |
| intercepts- and slopes-as-outcomes model | 截距與斜率結果模型 | 以截距與斜率為結果之模型 | 6 | 2 | 6 |
| interference | 單位間干擾 | 干擾 | 31 | 31 | 31 |
| intraclass correlation coefficient (ICC) | 組內相關係數 | 1 | 1 | 30 | |
| intraindividual standard deviation | 個人內標準差 | 28 | 28 | 28 | |
| inverse matrix | 反矩陣 | – | 9 | A | |
| item difficulty and easiness | 試題難度與容易度 | 30 | 30 | 30 | |
| item response theory (IRT) | 試題反應理論 | – | 8 | 30 | |
| iterative generalized least squares (IGLS) | 迭代廣義最小平方法 | 疊代廣義最小平方法 | 9 | 9 | 9 |
| J | |||||
| Johnson–Neyman region | Johnson–Neyman 區域 | 6 | 6 | 6 | |
| joint modeling imputation | 聯合建模插補 | 17 | 17 | 17 | |
| Journal Article Reporting Standards for Quantitative Research (JARS-Quant) | 量化研究期刊論文報告標準 | APA 量化研究報告標準 | 18 | 18 | 18 |
| K | |||||
| Kenward–Roger approximation | Kenward–Roger 近似法 | 10 | 9 | 10 | |
| key (identifier) | 識別碼(鍵) | 鍵值;索引鍵 | 4 | 4 | 4 |
| knot | 節點 | 結點 | 19 | 4 | 19 |
| Kronecker product | Kronecker 積 | 克羅內克積 | – | A | A |
| L | |||||
| lagged predictor | 延宕預測變項 | 21 | 21 | 21 | |
| language-as-fixed-effect fallacy | 語言作為固定效果之謬誤 | 26 | 26 | 26 | |
| Laplace approximation | 拉普拉斯近似 | 23 | 13 | 23 | |
| lasso | 套索迴歸 | Lasso | 32 | 32 | 32 |
| latent and observed-mean centering | 潛在平減與觀察平均數平減 | 潛在中心化 | 21 | 21 | 21 |
| latent-basis model | 潛在基底模型 | 22 | 22 | 22 | |
| latent class | 潛在類別 | – | 2 | 22 | |
| latent group mean | 潛在組平均數 | – | 7 | 21 | |
| latent growth curve model | 潛在成長曲線模型 | 22 | 19 | 22 | |
| latent intraclass correlation | 潛在組內相關 | 潛在組內相關係數 | 30 | 30 | 30 |
| latent regression | 潛在迴歸 | 30 | 30 | 30 | |
| latent response variable | 潛在反應變項 | 23 | 23 | 23 | |
| latent-scale ICC | 潛在尺度 ICC | 潛在尺度組內相關係數 | 23 | 23 | 23 |
| latent variable | 潛在變項 | – | 1 | 29 | |
| league table | 排行榜 | 排名表 | 12 | 12 | 12 |
| leave-one-out cross-validation (LOO) | 留一交叉驗證 | – | 13 | 13 | |
| level-1 and level-2 files | 第一層與第二層資料檔 | 層次一與層次二檔案 | 4 | 4 | 4 |
| level-1 model and level-2 model | 第一層模型與第二層模型 | 層次一模型與層次二模型;階層一模式與階層二模式 | 2 | 1 | 14 |
| level-2 (empirical Bayes) residual | 第二層殘差(經驗貝氏殘差) | 層次二殘差 | 15 | 12 | 15 |
| level-2 heteroscedasticity | 第二層變異數異質性 | 層次二變異數異質性 | 15 | 15 | 15 |
| level-2 predictor | 第二層預測變項 | 層次二預測變項 | 5 | 2 | 5 |
| level-2 weight | 第二層權數 | 層次二權數;叢集權數 | 17 | 17 | 17 |
| level-3 variance | 第三層變異數 | 層次三變異數 | 8 | 8 | 8 |
| level (of a hierarchy) | 層次 | 層級 | 1 | 1 | 8 |
| level-specific fit | 層次別適配度 | 分層適配度 | 29 | 29 | 29 |
| level-specific reliability | 層次別信度 | 分層信度 | 30 | 30 | 30 |
| leverage | 槓桿值 | – | 10 | 15 | |
| life table | 生命表 | 25 | 25 | 25 | |
| likelihood | 概似 | 概似函數 | – | 1 | 9 |
| likelihood-ratio test | 概似比檢定 | 10 | 6 | 10 | |
| linear logistic test model (LLTM) | 線性邏輯斯測驗模型 | 30 | 30 | 30 | |
| linear predictor | 線性預測子 | 線性預測式 | 24 | 23 | 24 |
| link function | 連結函數 | 24 | 23 | 23 | |
| listwise deletion | 表列刪除 | 完全刪除法 | 17 | 17 | 17 |
| LKJ prior | LKJ 先驗分配 | 13 | 13 | 13 | |
| local independence | 局部獨立 | 30 | 30 | 30 | |
| local maximum | 局部極大值 | 局部最大值 | 8 | 8 | 9 |
| location-scale correlation | 位置-尺度相關 | 28 | 28 | 28 | |
| location-scale model | 位置-尺度模型 | 28 | 15 | 28 | |
| log-likelihood | 對數概似 | – | 5 | 9 | |
| log-linear variance function (variance model) | 對數線性變異數函數 | 對數線性變異數模型 | 15 | 15 | 15 |
| logistic regression | 邏輯斯迴歸 | 羅吉斯迴歸 | – | 23 | 23 |
| logit | 勝算對數 | 對數勝算 | – | 17 | 24 |
| long and wide format | 長格式與寬格式 | 4 | 4 | 4 | |
| longitudinal data | 縱貫性資料 | 縱貫資料;追蹤資料 | – | 1 | 21 |
| M | |||||
| macro-level and micro-level propositions | 鉅觀層次與微觀層次命題 | 巨觀與微觀層次命題 | 1 | 1 | 1 |
| macro-to-micro and micro-to-macro propositions | 鉅觀-微觀命題 | 巨觀-微觀命題 | 1 | 1 | 1 |
| manifest aggregation | 外顯聚合 | – | 7 | 7 | |
| many-to-one merge | 多對一合併 | 4 | 4 | 4 | |
| marginal and conditional R-squared | 邊際與條件 R 平方 | 11 | 5 | 11 | |
| marginal covariance matrix | 邊際共變數矩陣 | 2 | 2 | 26 | |
| marginal likelihood | 邊際概似 | 邊際概度 | 9 | 9 | B |
| marginal model | 邊際模型 | 2 | 1 | 2 | |
| marginal residual | 邊際殘差 | 15 | 15 | 15 | |
| Markov chain Monte Carlo (MCMC) | 馬可夫鏈蒙地卡羅法 | 13 | 13 | 13 | |
| maximal random-effects structure | 最大隨機效果結構 | 26 | 14 | 26 | |
| maximum likelihood (ML) | 最大概似估計 | 最大概似法 | – | 1 | 9 |
| mean and covariance structure | 平均數與共變數結構 | 14 | 4 | 15 | |
| means-by-covariate display | 依共變項分組平均數圖 | 4 | 4 | 4 | |
| measurement error | 測量誤差 | 20 | 7 | 20 | |
| measurement invariance | 測量不變性 | 測量恆等性 | – | 22 | 22 |
| median lifetime | 中位存活時間 | 25 | 25 | 25 | |
| median odds ratio | 中位數勝算比 | 23 | 23 | 23 | |
| mediation | 中介效果 | 中介作用 | – | 22 | 29 |
| mediation design (1-1-1, 2-1-1, 2-2-1, 1-1-2) | 中介設計 | 29 | 29 | 29 | |
| membership weight | 隸屬權數 | 26 | 1 | 26 | |
| meta-analysis | 後設分析 | 統合分析 | 27 | 1 | 27 |
| meta-regression | 後設迴歸 | 統合迴歸 | 27 | 27 | 27 |
| method-of-moments estimator | 動差法估計式 | 動差估計量 | 3 | 3 | 3 |
| min | min | 26 | 26 | 26 | |
| minimum detectable effect size (MDES) | 最小可偵測效果量 | 16 | 16 | 16 | |
| missing at random (MAR) | 隨機遺漏 | 17 | 17 | 17 | |
| missing completely at random (MCAR) | 完全隨機遺漏 | 17 | 17 | 17 | |
| missing data | 遺漏資料 | 遺漏值;缺失資料 | – | 1 | 17 |
| missing not at random (MNAR) | 非隨機遺漏 | 17 | 17 | 17 | |
| mixed-effects location-scale model (MELS) | 混合效果位置-尺度模型 | 28 | 21 | 28 | |
| mixed-effects model (linear mixed model) | 混合效果模型 | 混合模型 | 1 | 1 | 30 |
| mixed-model equations | 混合模型方程式 | 12 | 12 | 12 | |
| mixing edge | 混合邊 | 22 | 2 | 22 | |
| mixture of normals | 常態混合分配 | 常態分配的混合 | 28 | 12 | 28 |
| model-based covariance matrix | 模型基礎共變數矩陣 | 10 | 3 | 10 | |
| model-based inference | 模型基礎推論 | 17 | 17 | 17 | |
| model-based recursive partitioning | 模型基礎遞迴分割 | 32 | 32 | 32 | |
| model-building record | 建模紀錄 | 模型建構紀錄 | 14 | 14 | 14 |
| model comparison | 模型比較 | – | 5 | 5 | |
| model-comparison table | 模型比較表 | 18 | 5 | 18 | |
| model fit (fit index) | 模型適配度(適配度指標) | – | 11 | 22 | |
| model-implied data display | 模型隱含資料圖 | 模型推導資料圖 | 2 | 2 | 2 |
| moderation | 調節效果 | 干擾效果 | – | 6 | 27 |
| Monte Carlo confidence interval | 蒙地卡羅信賴區間 | 29 | 29 | 29 | |
| Monte Carlo simulation | 蒙地卡羅模擬 | – | 1 | 29 | |
| Monte Carlo standard error | 蒙地卡羅標準誤 | 16 | 1 | 19 | |
| moving average (MA(1)) | 移動平均 | 移動平均數 | 20 | 20 | 20 |
| multilevel item response model | 多層次試題反應模型 | 30 | 30 | 30 | |
| multilevel latent covariate model | 多層次潛在共變項模型 | 7 | 7 | 7 | |
| multilevel model | 多層次模型 | 多層次模式;多層級模型 | 1 | 1 | 3 |
| multilevel structural equation model (MSEM) | 多層次結構方程模型 | 29 | 1 | 29 | |
| multiple imputation | 多重插補 | 多重設算 | 17 | 17 | 17 |
| multiple-membership model | 多重隸屬模型 | 多重成員模型 | 1 | 1 | 26 |
| multiple-membership multiple-classification (MMMC) model | 多重隸屬多重分類模型 | 26 | 26 | 26 | |
| multiple spells | 多重時段 | 多重期間 | 25 | 25 | 25 |
| multisite trial | 多地點試驗 | 多場域試驗 | 16 | 16 | 16 |
| multistage sampling | 多階段抽樣 | 1 | 1 | 1 | |
| multivariate multilevel model | 多變量多層次模型 | 27 | 22 | 27 | |
| multivariate normal distribution | 多變量常態分配 | – | 9 | A | |
| Mundlak model | Mundlak 模型 | 7 | 7 | 7 | |
| N | |||||
| negative binomial model | 負二項模型 | 24 | 24 | 24 | |
| negative variance estimate | 負變異數估計值 | 9 | 9 | 9 | |
| nested data | 巢套資料 | 巢狀資料 | 26 | 1 | 1 |
| Newton–Raphson algorithm | 牛頓-拉弗森法 | 9 | 9 | 9 | |
| Nickell bias | Nickell 偏誤 | 21 | 21 | 21 | |
| no pooling | 不合併 | 3 | 3 | 3 | |
| nominal outcome (multinomial logit) | 名義結果變項(多項邏輯斯模型) | 名目變項;多項邏輯式模型 | – | 24 | 24 |
| non-centered parameterization | 非中心化參數化 | 13 | 13 | 13 | |
| non-hierarchical data | 非階層資料 | 26 | 26 | 26 | |
| noncentral t distribution | 非中心 t 分配 | 16 | 16 | 16 | |
| noninformative censoring | 不具訊息的設限 | 非訊息性設限 | 25 | 25 | 25 |
| normal distribution | 常態分配 | 常態分布 | – | 2 | 10 |
| normality | 常態性 | – | 9 | 15 | |
| O | |||||
| observation-level random effect (OLRE) | 觀察值層次隨機效果 | 24 | 24 | 24 | |
| occasion (of measurement) | 測量時間點 | 測量場次 | – | 1 | 20 |
| odds ratio | 勝算比 | 23 | 23 | 23 | |
| offset | 偏移項 | 抵銷項 | 24 | 24 | 24 |
| omitted variable | 遺漏變項 | 遺漏變數 | – | 7 | 7 |
| one-step approximation | 單步近似 | 一步近似 | 15 | 15 | 15 |
| optimal cluster size | 最適叢集大小 | 最佳叢集大小 | 16 | 16 | 16 |
| ordinal outcome | 次序結果變項 | 順序變項 | – | 1 | 24 |
| ordinary least squares (OLS) | 普通最小平方法 | – | 1 | 4 | |
| origin of time | 時間原點 | 19 | 18 | 19 | |
| orthogonal polynomial | 正交多項式 | – | 19 | 19 | |
| overdispersion | 過度離散 | 24 | 24 | 24 | |
| overextraction of classes | 類別過度萃取 | 過度抽取類別 | 22 | 22 | 22 |
| P | |||||
| pairwise data structure | 成對資料結構 | 27 | 27 | 27 | |
| panel data | 追蹤資料 | 縱橫資料;面板資料 | – | 7 | 7 |
| parallel-lines assumption | 平行線假定 | 5 | 5 | 5 | |
| parallel-process model | 平行歷程模型 | 22 | 22 | 22 | |
| parallel trends assumption | 平行趨勢假定 | 31 | 31 | 31 | |
| parameter promotion | 參數提升 | 2 | 2 | 2 | |
| parametric bootstrap | 參數拔靴法 | 10 | 10 | 10 | |
| Pareto-smoothed importance sampling LOO (PSIS-LOO) | 帕累托平滑重要抽樣留一交叉驗證 | 13 | 13 | 13 | |
| parsimonious random part | 精簡隨機部分 | 簡約隨機部分 | 14 | 11 | 14 |
| partial pooling | 部分合併 | 3 | 3 | 3 | |
| partial proportional odds | 部分比例勝算 | 24 | 24 | 24 | |
| path diagram | 路徑圖 | – | 2 | 2 | |
| pattern-mixture model | 型態混合模型 | 模式混合模型 | 17 | 17 | 17 |
| penalized quasi-likelihood (PQL) | 懲罰準概似 | 23 | 13 | 23 | |
| person-mean centering | 個人平減 | 個人平均數中心化 | – | 19 | 21 |
| person-period data | 人-期資料 | 個人-時期資料 | 25 | 25 | 25 |
| piecewise growth model | 分段成長模型 | 19 | 19 | 19 | |
| plate (in a model graph) | 板塊 | 1 | 1 | D | |
| plates as loops | 板塊即迴圈 | 4 | 4 | 4 | |
| plausible values | 可能值 | 似真值 | 17 | 15 | 17 |
| Poisson regression | 卜瓦松迴歸 | – | 24 | 24 | |
| polynomial | 多項式 | 4 | 4 | 19 | |
| pooled within-cluster slope | 合併組內斜率 | 匯合組內斜率 | 3 | 1 | 3 |
| population-averaged effect | 母群平均效果 | 23 | 2 | 25 | |
| positive definite matrix | 正定矩陣 | – | 6 | A | |
| posterior distribution | 後驗分配 | 事後分配 | 12 | 9 | 13 |
| posterior predictive check | 後驗預測檢核 | 13 | 13 | 13 | |
| posterior predictive p-value | 後驗預測 p 值 | 13 | 13 | 13 | |
| potential outcomes | 潛在結果 | 31 | 31 | 31 | |
| potential scale reduction factor () | 潛在尺度縮減因子 | 13 | 13 | 13 | |
| power curve | 檢定力曲線 | 16 | 16 | 16 | |
| precision weights | 精確度權數 | 17 | 17 | 17 | |
| predicted-values plot | 預測值圖 | 18 | 18 | 18 | |
| prediction error variance | 預測誤差變異數 | 12 | 11 | 12 | |
| prediction interval | 預測區間 | 27 | 12 | 27 | |
| prediction of random effects | 隨機效果預測 | 隨機效果的預測值 | 12 | 11 | 32 |
| preliminary fixed part | 初步固定部分 | 4 | 4 | 14 | |
| preliminary random part | 初步隨機部分 | 14 | 14 | 14 | |
| preregistration | 預先註冊 | 預註冊 | 18 | 16 | 18 |
| prior distribution | 先驗分配 | 事前分配 | 12 | 1 | 13 |
| prior predictive check | 先驗預測檢核 | 13 | 13 | 13 | |
| profile likelihood | 剖面概似 | – | 9 | 9 | |
| profile likelihood interval | 剖面概似區間 | 剖面概似信賴區間 | 10 | 10 | 13 |
| profiled deviance | 剖面離異數 | 9 | 9 | 9 | |
| projection matrix | 投影矩陣 | – | 32 | A | |
| propensity score | 傾向分數 | 31 | 31 | 31 | |
| proportion of variance explained | 變異解釋比例 | 解釋變異量 | – | 1 | 11 |
| proportional hazards (proportionality) assumption | 比例風險假定 | 25 | 25 | 25 | |
| proportional odds model | 比例勝算模型 | 24 | 24 | 24 | |
| proportional reduction in variance | 變異數減少比例 | 變異數縮減比例 | 5 | 5 | 11 |
| pseudo- | 擬 R 平方 | 虛擬 R 平方;擬判定係數 | 19 | 19 | 19 |
| pseudo-maximum likelihood (PML) | 擬最大概似估計 | 虛擬最大概似估計 | 17 | 17 | 17 |
| Q | |||||
| quadratic growth | 二次成長 | – | 18 | 19 | |
| R | |||||
| R-squared of each cluster and meta R-squared (, ) | 各叢集 R 平方與整體 R 平方 | 14 | 14 | 14 | |
| random coefficient | 隨機係數 | – | 1 | D | |
| random effect | 隨機效果 | 隨機效應 | 2 | 1 | 24 |
| random effect of a categorical predictor | 類別預測變項的隨機效果 | 6 | 6 | 6 | |
| random-effects ANOVA | 隨機效果變異數分析 | 隨機效應變異數分析 | 3 | 1 | 3 |
| random-effects assumption | 隨機效果假定 | 7 | 7 | 7 | |
| random-effects meta-analysis | 隨機效果後設分析 | 隨機效果統合分析 | 27 | 27 | 27 |
| random forest | 隨機森林 | – | 32 | 32 | |
| random indirect effect | 隨機間接效果 | 29 | 29 | 29 | |
| random innovation variance | 隨機新息變異數 | 21 | 20 | 21 | |
| random intercept | 隨機截距 | – | 1 | 5 | |
| random intercept cross-lagged panel model (RI-CLPM) | 隨機截距交叉延宕模型 | 21 | 21 | 21 | |
| random scale effect | 隨機尺度效果 | 28 | 28 | 28 | |
| random slope | 隨機斜率 | 6 | 1 | 6 | |
| rank interval | 排名區間 | 名次區間 | 12 | 12 | 12 |
| rank plot | 等級圖 | 13 | 13 | 13 | |
| Rasch model | Rasch 模型 | 30 | 30 | 30 | |
| rate of change | 變化率 | 19 | 16 | 19 | |
| rate ratio | 率比 | 發生率比 | 24 | 24 | 24 |
| raw score | 原始分數 | 7 | 7 | 7 | |
| recurrent events | 重複事件 | 復發事件;重現事件 | 25 | 25 | 25 |
| regression discontinuity design | 不連續迴歸設計 | 迴歸不連續設計 | 31 | 31 | 31 |
| regression tree (decision tree) | 迴歸樹 | 決策樹 | – | 32 | 32 |
| regularization | 正規化 | 正則化 | – | 32 | 32 |
| relative covariance factor | 相對共變數因子 | 9 | 9 | 9 | |
| reliability | 信度 | 5 | 1 | 30 | |
| reliability of a cluster mean | 組平均數信度 | 組平均數的信度 | 5 | 5 | 7 |
| repeated measures | 重複測量 | 1 | 1 | 19 | |
| reporting checklist | 報告檢核表 | 18 | 5 | 18 | |
| reproducibility | 可重現性 | 再現性 | – | 4 | 18 |
| residual | 殘差 | – | 1 | 20 | |
| residual regressions | 殘差迴歸 | 14 | 14 | 14 | |
| restricted maximum likelihood (REML) | 限制最大概似估計 | 殘差最大概似估計 | 9 | 1 | 9 |
| ridge regression (ridge penalty) | 脊迴歸 | 32 | 32 | 32 | |
| Rights–Sterba decomposition | Rights–Sterba 分解 | 11 | 11 | 11 | |
| robust standard error | 穩健標準誤 | – | 3 | 10 | |
| robust variance estimation (RVE) | 穩健變異數估計 | 27 | 27 | 27 | |
| root mean squared error (RMSE) | 均方根誤差 | – | 7 | 31 | |
| Rubin’s rules | Rubin 合併規則 | Rubin 法則 | 17 | 17 | 17 |
| S | |||||
| same-class and same-school correlation | 同班相關與同校相關 | 8 | 8 | 8 | |
| sampling error | 抽樣誤差 | – | 2 | 27 | |
| sampling weight | 抽樣權數 | 抽樣權重 | 17 | 15 | 17 |
| sandwich estimator | 三明治估計式 | 三明治估計量 | 10 | 3 | 10 |
| Satterthwaite approximation | Satterthwaite 近似法 | 10 | 1 | 10 | |
| saturated model | 飽和模型 | 22 | 22 | 22 | |
| second-order growth model | 二階成長模型 | 二階潛在成長模型 | 22 | 22 | 22 |
| selection effect of frailty | 脆弱性的選擇效果 | 25 | 25 | 25 | |
| selection model | 選擇模型 | 17 | 17 | 17 | |
| self-consistency check | 自我一致性檢核 | 18 | 18 | 18 | |
| sensitivity analysis | 敏感度分析 | 敏感性分析 | 15 | 10 | 17 |
| serial correlation | 序列相關 | 20 | 15 | 20 | |
| shared and configural properties (constructs) | 共享屬性與組態屬性 | 共享特性與構形特性 | 30 | 29 | 30 |
| shared frailty | 共享脆弱性 | 25 | 25 | 25 | |
| shared-parameter model | 共享參數模型 | 17 | 17 | 17 | |
| shrinkage | 收縮 | 縮減 | 5 | 3 | 12 |
| simple slope | 簡單斜率 | 6 | 6 | 6 | |
| Simpson’s paradox | 辛普森悖論 | 辛普森詭論;辛普森矛盾 | 1 | 1 | 1 |
| simulation-based power | 模擬基礎檢定力 | 循模擬檢定力分析 | 16 | 16 | 16 |
| simulation-based residuals | 模擬基礎殘差 | 以模擬為基礎的殘差 | 23 | 23 | 23 |
| simulation envelope | 模擬包絡 | 模擬包絡帶 | 15 | 15 | 15 |
| simulation study | 模擬研究 | – | 4 | C | |
| simulation template | 模擬範本 | 模擬模板 | 4 | 4 | 4 |
| single-step adjustment | 單步校正 | 單一步驟校正 | 10 | 10 | 10 |
| singleton cluster | 單一觀察值叢集 | 4 | 4 | 4 | |
| singular fit | 奇異配適 | 奇異解 | 6 | 4 | 9 |
| slope variance | 斜率變異數 | 6 | 2 | 20 | |
| slopes-as-outcomes model | 斜率結果模型 | 以斜率為結果之模型 | 2 | 2 | 2 |
| small-sample correction | 小樣本校正 | – | 3 | 10 | |
| small-study effects | 小型研究效果 | 小型研究效應 | 27 | 27 | 27 |
| Snijders–Bosker | Snijders–Bosker R 平方 | 11 | 5 | 11 | |
| softmax function | softmax 函數 | 正規化指數函數;歸一化指數函數 | 24 | 24 | 24 |
| spaghetti plot (display) | 義大利麵圖 | 4 | 2 | 4 | |
| sphericity | 球形性 | 19 | 19 | 19 | |
| spline (regression spline) | 仿樣函數 | 樣條函數 | 4 | 4 | 4 |
| stable unit treatment value assumption (SUTVA) | 穩定單元處理值假定 | – | 31 | 31 | |
| stacked data | 堆疊資料 | 27 | 25 | 27 | |
| standard error | 標準誤 | – | 1 | 10 | |
| standardization within persons | 個人內標準化 | 21 | 21 | 21 | |
| standardized mean difference | 標準化平均數差異 | 標準化平均差 | 11 | 11 | 11 |
| stationarity (stationary process) | 定態性 | 平穩性 | 20 | 20 | 20 |
| statistical power | 統計檢定力 | 檢定力;統計考驗力 | – | 4 | 16 |
| stimuli as a random factor | 刺激作為隨機因子 | 26 | 1 | 26 | |
| stratification | 分層 | – | 17 | 17 | |
| stress reactivity | 壓力反應性 | 21 | 21 | 21 | |
| structural equation model (SEM) | 結構方程模型 | 結構方程模式 | – | 1 | 29 |
| subject-specific (cluster-specific) effect | 個體特定效果 | 叢集特定效果 | 23 | 2 | 2 |
| substantive-model-compatible imputation | 實質模型相容插補 | 17 | 17 | 17 | |
| survival analysis | 存活分析 | 25 | 25 | 25 | |
| survival function | 存活函數 | 25 | 25 | 25 | |
| T | |||||
| test of distinguishability | 可區辨性檢定 | 27 | 27 | 27 | |
| three-level growth model | 三層次成長模型 | 8 | 8 | 8 | |
| three-level meta-analysis | 三層次後設分析 | 三層次統合分析 | 27 | 27 | 27 |
| three-level model | 三層次模型 | 1 | 1 | 8 | |
| threshold | 閾值 | 門檻值 | 24 | 24 | 24 |
| time-invariant covariate (predictor) | 不隨時間變動的共變項 | 19 | 19 | 19 | |
| time scores (loadings) | 時間分數(負荷量) | 22 | 22 | 22 | |
| time-structured data | 時間結構化資料 | 19 | 19 | 19 | |
| time-varying covariate (predictor) | 隨時間變動的共變項 | 時變共變項 | 19 | 4 | 19 |
| Toeplitz structure | Toeplitz 結構 | 20 | 20 | 20 | |
| top-down and step-up model building | 由上而下與逐步增加建模 | 由上而下與由下而上建模 | 14 | 14 | 14 |
| total effect (total relation, total regression) | 總效果(總關係) | 總迴歸 | 1 | 1 | 3 |
| transition model | 轉移模型 | 19 | 19 | 19 | |
| trellis display | 格子圖 | 格狀圖 | 4 | 4 | 4 |
| two-intercept model | 雙截距模型 | 27 | 27 | 27 | |
| two-parameter logistic (2PL) model | 二參數邏輯斯模型 | 二參數對數模式 | 30 | 30 | 30 |
| two-stage approach (stage-one and stage-two regressions) | 兩階段法(第一階段與第二階段迴歸) | 二階段估計 | 3 | 2 | 3 |
| Type I error | 第一類型錯誤 | 型一錯誤 | – | 1 | 14 |
| U | |||||
| unconditional growth model | 無條件成長模型 | 19 | 19 | 19 | |
| unconditional means model | 無條件平均數模型 | 空模型 | 19 | 19 | 19 |
| Unified Model Graph (UMG) | 統一模型圖 | 1 | 1 | 2 | |
| unit-average and cluster-average effects | 單位平均效果與叢集平均效果 | 31 | 31 | 31 | |
| unit diagram | 單位圖 | 1 | 1 | 26 | |
| unit of analysis | 分析單位 | – | 1 | 1 | |
| unstructured covariance matrix | 無結構共變數矩陣 | 未結構化共變數矩陣 | 20 | 2 | 20 |
| V | |||||
| variable indicator (multivariate model) | 變項指示變項 | 27 | 27 | 27 | |
| variance components | 變異成分 | 變異數成分 | – | 1 | 11 |
| variance-covariance matrix | 變異數-共變數矩陣 | – | 2 | 10 | |
| variance function | 變異數函數 | 2 | 2 | 6 | |
| variance partition coefficient (VPC) | 變異分割係數 | 8 | 8 | 26 | |
| variogram | 變異圖 | 序列變異圖;變異函數 | 20 | 20 | 20 |
| W | |||||
| Wald chi-square statistic | Wald 卡方統計量 | Wald 卡方檢定 | 10 | 10 | 10 |
| Wald test (Wald statistic) | Wald 檢定 | 10 | 3 | 10 | |
| weakly informative prior | 弱訊息先驗分配 | 13 | 9 | 13 | |
| widely applicable information criterion (WAIC) | 渡邊-赤池訊息準則 | 廣義赤池訊息準則 | 13 | 13 | 13 |
| within-between (hybrid) model | 組內-組間模型 | 7 | 5 | 7 | |
| within-cluster and between-cluster covariance matrices | 組內與組間共變數矩陣 | 組內與組間共變數 | 27 | 27 | 27 |
| within-cluster effect (within slope) | 組內效果 | 群內效果 | 7 | 1 | 7 |
| within-group agreement | 組內一致性 | 30 | 30 | 30 | |
| within-level and between-level interaction | 組內層次與組間層次交互作用 | 層次內與層次間交互作用 | 29 | 29 | 29 |
| within-person and between-person effects | 個人內效果與個人間效果 | 19 | 19 | 21 | |
| within-person change and within-person fluctuation | 個人內改變與個人內波動 | 21 | 19 | 21 | |
| within-person variability | 個人內變異性 | 28 | 14 | 21 | |
| working correlation | 工作相關矩陣 | 任意選定相關矩陣 | 32 | 3 | 32 |
| Z | |||||
| zero-inflated model | 零膨脹模型 | 24 | 24 | 24 | |
Note. Key: first chapter in which the term, or an inflected form of it, is printed in bold or listed among the chapter’s key terms (– if it is a key term only as part of a longer term or not at all); First: chapter in which the term first occurs in the running text; Main: chapter with the most occurrences (the earlier chapter on ties); numbers are chapters, letters are appendices. All three were found by a search of the chapter sources with Scripts/AppF/appF_glossary_V02.R; abbreviations in parentheses were searched as well, except HLM, which also names a program.