文章介紹與資料來源
司法院針對殺人罪、毒品犯罪、搶奪強盜及妨害性自主等社會矚目案件設有「量刑資訊系統」及「量刑趨勢建議系統」，提供實務界法官論罪科刑的其一依據。惟前者的資訊系統過於制式化，編碼人員的編碼程序不夠縝密，量刑因子的精確性亦有待提升。後者系統則係以統計迴歸方式分析實務判決資料後，依政府機關、學術單位及民間團體等焦點團體建議，調整量刑因子及影響力大小製作而成。亦可見該系統人為應然介入之因素過多，無法客觀分析法官於判決量刑時實際參酌之量刑因子為何。
故本文嘗試搜索民國106年1月至107年7月共計514則有關殺人罪或相關死亡結果（包括傷害致死、重傷害致死、殺直系血親尊親屬、傷直系血親尊親屬致死等）的刑事判決。分析該犯罪所適用的法條、法定加重減輕事由、以及刑法第57條各款之科刑審酌事項，是否對於法官科處有期徒刑之刑度有所影響。進而觀察近一～二年法官審酌殺人相關刑事案件時所實際參酌之量刑因子，提供實務界對於殺人案件的量刑標準有一定之理解。
文獻回顧
本文閱讀近十年來有關殺人罪相關量刑研究的學術著作。其中余麗貞（2010）〈臺灣地區殺人案件量刑因素之研究〉針對民國92到97年全國二十個地方法院，六年間所有殺人既遂、未遂以及預備殺人之案件進行分析。分析的自變項包括法定及其他非法定量刑因子（例如：被害人的性別、國籍、年齡等）。其中，自變項分為「被告」、「犯罪行為」、「被害人」及「法官」等四個類型。再透過描述統計、變異數分析以及多元類別分析，解釋各因素與法官量刑之間是否有顯著相關。然該文結論認為被告「自首」、「自白」、「是否精神耗弱」、「犯罪手法」、「犯罪人數」以及「既遂/未遂」等因素對於法官量刑皆有顯著影響。
蔡彩貞（2012）〈殺人罪量刑之實證研究〉則針對民國85年到93年九年間司法院所公佈二百二十個殺人既遂之有罪判決進行分析。以刑法第二百七十一條第一項殺人既遂罪、同法第五十七條之科刑審酌，以及作者個人從事刑事審判之實務經驗，定出殺人案件中可能影響法官量刑的35個自變項（例如：精神狀態、年齡、手段、與被害人關係、自白、和解、賠償、累犯與否等）。另外，將量刑加重事由設為「正向」，減輕事由設為「負向」。於統計方法上，使用描述統計計算各自變數在判決書中出現之次數、以及有期徒刑、無期徒刑及死刑的案件數量。再使用卡方檢定分析法官「宣告主刑種類」與各影響因素之間關係是否顯著。最後，再分兩階段進行迴歸分析：第一階段觀察法官選擇之主刑種類（有期徒刑、無期徒刑或死刑），第二階段再針對有期徒刑之刑度作迴歸。然該研究發現影響量刑之變項包括：「是否可歸責被害人」、被告「是否酒後或相類似情形」、「自首」、「手段預謀」、「對被害人施以救護」、「非累犯」等。
另外，許旭聖（2015）〈從我國殺人罪審判實務的量刑因子分析：論性別對科刑的影響〉一文針對「性別」對於科刑之影響進行分析，以「問卷調查」、「判決統計」等研究方法發現多數法官不會因為被告或被害人的性別不同而影響量刑；惟會因為被告的年齡、職業、學歷，與被害人的年齡而受影響。另，法官的量刑考量大多係根據法定因素（例如：刑法57條），很少著墨非法定因素的影響，亦無所謂女性法官量刑較輕之現象。
陳玉書、林健陽、賴宏信、郭豫珍（2011）〈殺人罪量刑準則之實證分析〉一文則分析2001-2008年共500件台灣各地方法院殺人罪判決。以描述統計、卡方檢定及羅吉斯迴歸等統計方式發現：量處無期徒刑之案件多以刑法第57條中「無悔悟」、「無和解」、「無宥恕」、「無被害者刺激」、「精神狀況正常」等因素審酌量刑。
綜此，有鑒於過往之學術研究者大多具有刑事審判實務，可針對自身在實務判決中所參酌之非法定事由進行分析。本文擬以法官實際於判決書中所書寫的量刑因子，包括：犯罪所適用的條文、法定加重減輕事由以及刑法第57條各款之科刑審酌事項，分析近一～兩年法官於殺人相關案件中審酌的量刑因子為何。盡量避免過多之人為因素，進行客觀中立、實然層面的法官量刑行為分析。
變項設計
應變項：
1. 主刑種類
2. 有期徒刑刑度自變項：
1. 適用法條
2. 法定加重減輕事由
3. 刑法第57條各款編碼設計
應變項
1. 主型種類： 死刑=1 無期徒刑=2 有期徒刑=3
2. 有期徒刑刑度統一換算成「月」
自變項
1. 適用條文：
- 271 殺人既遂、殺人未遂
- 277第二項前段 傷害致死
- 278第二項前段 重傷致死
- 272 殺直系血親尊親屬罪
- 280 傷直系血親尊親屬致死罪
2. 法定事由：（適用1，未適用0）
法定加重事由：
刑法第47條累犯、兒童及少年福利與權益保障法第112條
法定減輕事由：
刑法第19條精神障礙或心智缺陷之減刑、第20條瘖啞之減刑、第23條但書防衛過當之減刑、第25條二項普通未遂之減刑、第27條一項中止犯之減刑、第59條情堪憫恕之減刑、第62條前段自首之減刑、
3. 刑法57條各款
（一）、犯罪之動機、目的
口角細故=1
感情=2
財務=3
精神異常=4
受暴=5 （包括言語暴力、精神暴力）
報仇=6
替人尋仇=7（替友尋仇或收錢辦事等）
脫免逮捕=8
不詳、無法歸類=9（二）、犯罪時所受之刺激
是（臨時起意）=0
否（預謀）=1（三）、犯罪之手段
1.工具：徒手=1 一般工具=2 槍砲彈藥刀械=3 縱火=4
2.單獨或共同犯罪：單獨=0 共同=1 共同但非主要參與=2（四）、犯罪行為人之生活狀況
1. 經濟狀況：貧寒=1 勉持=2 小康=3 中產=4 富裕=5 未提及=6（ 可能的作法：貧寒/非貧寒/未提及 ）
2. 是否負扶養責任：無=0 有=1 未提及=2
3. 有無職業：無=0 有=1 不固定=2 未提及=3
4. 是否已婚：未婚=0 已婚=1 其他=2（離婚、分居） 未提及=3（五）、犯罪行為人之品行
有無不適用累犯的前科：有=1 無=0（六）、犯罪行為人之智識程度
1. 最高學歷：
不識字=0
小學=1
國中=2
高中/高職=3
專科=4
大學=5
研究所=6
2. 有無精神疾病（不適用刑法19條）：
無=0
有=1（七）、犯罪行為人與被害人之關係
素不相識=1
家庭成員=2（家暴法之「家庭成員」＋未同居但（現在或過去曾）具有親密關係者）
其他=3（八）、犯罪行為人違反義務之程度–>只適用於過失犯
（九）、犯罪所生之危險或損害
1.沒事_人數
2.輕傷_人數
3.重傷_人數
4.死亡_人數
5.是否造成被害人心理創傷 是=1 否=0
6.是否造成社會治安影響（是否在公共場合） 是=1 否=0（十）、犯罪後之態度
1. 對於犯行：不認罪=0 坦承但無悔意=1 坦承且表達悔意=2 未提及=3
2. 與被害人（家屬）是否和、調解或受寬恕：無=0 有=1 部分=2 未提及=3描述統計
有期徒刑刑期盒鬚圖
（以適用法條為區分）
有期徒刑刑期盒鬚圖
（以既遂/未遂為區分）
迴歸分析
法定加重減輕事由
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62, data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -49.142 -11.179 -5.179 7.129 133.322
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 77.179 2.309 33.425 < 2e-16 ***
## plus_47 2.465 3.810 0.647 0.518785
## plus_112 29.499 8.344 3.535 0.000547 ***
## minus_192 -20.679 6.030 -3.429 0.000788 ***
## minus_271 -19.644 21.286 -0.923 0.357627
## minus_59 -35.721 6.964 -5.129 9.17e-07 ***
## minus_62 -23.231 6.139 -3.784 0.000225 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.04 on 145 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3182, Adjusted R-squared: 0.29
## F-statistic: 11.28 on 6 and 145 DF, p-value: 2.567e-10既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62, data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -111.115 -11.102 0.898 12.898 83.329
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 155.1015 4.0954 37.872 < 2e-16 ***
## factor(art)2 -58.4309 5.3443 -10.933 < 2e-16 ***
## factor(art)3 -71.7772 17.0934 -4.199 5.05e-05 ***
## factor(art)5 -36.0000 40.2935 -0.893 0.373336
## plus_47 20.0135 5.7317 3.492 0.000664 ***
## plus_112 8.8713 8.3221 1.066 0.288482
## minus_192 0.8985 28.7846 0.031 0.975149
## minus_20 -23.3912 33.0364 -0.708 0.480235
## minus_23 -23.8116 17.6688 -1.348 0.180205
## minus_271 -107.7103 16.9003 -6.373 3.24e-09 ***
## minus_59 -64.5322 8.6950 -7.422 1.56e-11 ***
## minus_62 -18.1872 7.1217 -2.554 0.011858 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.49 on 125 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6921, Adjusted R-squared: 0.665
## F-statistic: 25.54 on 11 and 125 DF, p-value: < 2.2e-16犯罪之動機、目的
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(motive), data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -52.088 -10.874 -4.874 7.409 119.146
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 76.87438 2.89163 26.585 < 2e-16 ***
## plus_47 0.02765 3.92334 0.007 0.994386
## plus_112 35.18561 8.78942 4.003 0.000102 ***
## minus_192 -14.63973 6.91903 -2.116 0.036152 *
## minus_271 -16.90203 20.96323 -0.806 0.421474
## minus_59 -38.68343 7.18679 -5.383 3.07e-07 ***
## minus_62 -21.61191 6.08902 -3.549 0.000529 ***
## factor(motive)2 0.86491 6.06886 0.143 0.886881
## factor(motive)3 -0.85590 6.99781 -0.122 0.902831
## factor(motive)4 -15.07291 9.10469 -1.656 0.100093
## factor(motive)6 8.79390 7.10741 1.237 0.218082
## factor(motive)7 -4.00469 5.32763 -0.752 0.453521
## factor(motive)8 21.11377 8.20709 2.573 0.011150 *
## factor(motive)9 4.12562 14.89447 0.277 0.782202
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 20.66 on 138 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3741, Adjusted R-squared: 0.3151
## F-statistic: 6.345 on 13 and 138 DF, p-value: 2.713e-09既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(motive),
## data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -108.04 -10.50 0.00 14.48 85.72
##
## Coefficients: (1 not defined because of singularities)
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 153.5198 5.4740 28.045 < 2e-16 ***
## factor(art)2 -57.9866 5.8484 -9.915 < 2e-16 ***
## factor(art)3 -71.7731 17.6869 -4.058 8.93e-05 ***
## factor(art)5 -28.2789 41.9545 -0.674 0.50161
## plus_47 18.5194 6.0537 3.059 0.00275 **
## plus_112 5.3403 9.5185 0.561 0.57583
## minus_192 -5.2409 30.2455 -0.173 0.86273
## minus_20 -24.0824 34.5727 -0.697 0.48744
## minus_23 -18.9328 18.9343 -1.000 0.31940
## minus_271 -105.5816 17.6770 -5.973 2.53e-08 ***
## minus_59 -63.2755 9.2335 -6.853 3.50e-10 ***
## minus_62 -17.7568 7.5778 -2.343 0.02079 *
## factor(motive)2 0.1442 11.0596 0.013 0.98962
## factor(motive)3 -0.7214 10.3097 -0.070 0.94433
## factor(motive)4 NA NA NA NA
## factor(motive)5 -13.8540 19.0257 -0.728 0.46795
## factor(motive)6 7.7211 8.3522 0.924 0.35715
## factor(motive)7 4.3432 7.6008 0.571 0.56881
## factor(motive)8 10.8736 22.9400 0.474 0.63637
## factor(motive)9 6.9829 12.7452 0.548 0.58480
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 29.07 on 118 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6973, Adjusted R-squared: 0.6512
## F-statistic: 15.1 on 18 and 118 DF, p-value: < 2.2e-16犯罪所受之刺激
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + plan, data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -49.145 -11.189 -5.167 7.142 133.324
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 77.16669 3.08267 25.032 < 2e-16 ***
## plus_47 2.46887 3.88864 0.635 0.526506
## plus_112 29.48702 8.58358 3.435 0.000774 ***
## minus_192 -20.67769 6.05550 -3.415 0.000830 ***
## minus_271 -19.65765 21.48157 -0.915 0.361672
## minus_59 -35.71682 7.02068 -5.087 1.11e-06 ***
## minus_62 -23.23466 6.18489 -3.757 0.000249 ***
## plan 0.02209 3.60660 0.006 0.995122
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.11 on 144 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3182, Adjusted R-squared: 0.285
## F-statistic: 9.6 on 7 and 144 DF, p-value: 9.142e-10既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + plan,
## data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -112.648 -8.922 -0.296 14.164 84.338
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 152.9222 5.1948 29.438 < 2e-16 ***
## factor(art)2 -58.1374 5.3728 -10.821 < 2e-16 ***
## factor(art)3 -72.0727 17.1353 -4.206 4.94e-05 ***
## factor(art)5 -32.4886 40.7042 -0.798 0.426301
## plus_47 20.2144 5.7514 3.515 0.000615 ***
## plus_112 9.4026 8.3759 1.123 0.263789
## minus_192 -0.4335 28.9116 -0.015 0.988060
## minus_20 -21.9161 33.1769 -0.661 0.510105
## minus_23 -22.5118 17.8081 -1.264 0.208554
## minus_271 -107.0061 16.9675 -6.307 4.58e-09 ***
## minus_59 -64.0728 8.7393 -7.332 2.57e-11 ***
## minus_62 -17.4741 7.2126 -2.423 0.016850 *
## plan 3.5114 5.1312 0.684 0.495050
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.55 on 124 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6932, Adjusted R-squared: 0.6635
## F-statistic: 23.35 on 12 and 124 DF, p-value: < 2.2e-16犯罪之手段
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(tool) + factor(comp), data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -47.032 -11.392 -3.737 7.511 130.940
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 67.542 11.249 6.004 1.55e-08 ***
## plus_47 1.983 3.862 0.513 0.608417
## plus_112 30.028 8.478 3.542 0.000539 ***
## minus_192 -22.435 6.218 -3.608 0.000428 ***
## minus_271 -21.015 21.360 -0.984 0.326871
## minus_59 -36.266 7.009 -5.174 7.72e-07 ***
## minus_62 -21.501 6.483 -3.316 0.001160 **
## factor(tool)2 11.489 11.116 1.034 0.303106
## factor(tool)3 5.309 14.060 0.378 0.706290
## factor(comp)1 -2.542 3.938 -0.646 0.519545
## factor(comp)2 -15.359 12.992 -1.182 0.239126
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.07 on 141 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3348, Adjusted R-squared: 0.2876
## F-statistic: 7.095 on 10 and 141 DF, p-value: 5.515e-09既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(tool) +
## factor(comp), data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -112.289 -11.259 -0.627 13.112 92.031
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 144.5133 6.9056 20.927 < 2e-16 ***
## factor(art)2 -55.1944 5.7330 -9.628 < 2e-16 ***
## factor(art)3 -69.0303 17.2355 -4.005 0.000107 ***
## factor(art)5 -36.0000 40.2667 -0.894 0.373076
## plus_47 20.1721 5.7613 3.501 0.000649 ***
## plus_112 10.0644 8.5285 1.180 0.240283
## minus_192 -0.6265 28.9359 -0.022 0.982761
## minus_20 -22.8481 33.0215 -0.692 0.490316
## minus_23 -28.4122 17.9231 -1.585 0.115525
## minus_271 -109.7784 17.1065 -6.417 2.82e-09 ***
## minus_59 -63.0079 8.7897 -7.168 6.53e-11 ***
## minus_62 -16.7163 7.3399 -2.277 0.024515 *
## factor(tool)2 12.1133 6.1073 1.983 0.049588 *
## factor(tool)3 13.8449 21.2453 0.652 0.515852
## factor(comp)1 -0.5097 5.7381 -0.089 0.929361
## factor(comp)2 -0.1507 13.5042 -0.011 0.991113
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.47 on 121 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.7023, Adjusted R-squared: 0.6654
## F-statistic: 19.03 on 15 and 121 DF, p-value: < 2.2e-16犯罪行為人之生活狀況
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(econ) + factor(sup) + factor(job),
## data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -48.093 -11.594 -4.247 7.986 118.237
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 75.542 9.744 7.753 1.83e-12 ***
## plus_47 3.673 4.009 0.916 0.361274
## plus_112 26.050 8.423 3.092 0.002406 **
## minus_192 -26.231 6.276 -4.180 5.18e-05 ***
## minus_271 -14.426 21.261 -0.679 0.498587
## minus_59 -35.812 6.987 -5.126 9.89e-07 ***
## minus_62 -22.719 6.270 -3.624 0.000408 ***
## factor(econ)2 20.172 9.213 2.189 0.030262 *
## factor(econ)3 23.445 10.725 2.186 0.030513 *
## factor(econ)6 17.614 8.358 2.108 0.036892 *
## factor(sup)1 -6.391 6.273 -1.019 0.310090
## factor(sup)2 -11.563 5.900 -1.960 0.052059 .
## factor(job)1 -10.840 5.847 -1.854 0.065893 .
## factor(job)2 -20.643 10.929 -1.889 0.061022 .
## factor(job)3 -3.222 6.429 -0.501 0.617039
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 20.74 on 137 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3739, Adjusted R-squared: 0.3099
## F-statistic: 5.844 on 14 and 137 DF, p-value: 7.22e-09既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(econ) +
## factor(sup) + factor(job), data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -112.093 -12.175 -0.175 14.798 77.533
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 117.477 24.126 4.869 3.54e-06 ***
## factor(art)2 -55.918 5.708 -9.796 < 2e-16 ***
## factor(art)3 -68.232 17.491 -3.901 0.00016 ***
## factor(art)5 -36.000 39.613 -0.909 0.36533
## plus_47 17.708 6.103 2.902 0.00444 **
## plus_112 8.067 8.385 0.962 0.33805
## minus_192 16.895 29.948 0.564 0.57374
## minus_20 -26.287 34.684 -0.758 0.45004
## minus_23 -11.459 17.867 -0.641 0.52254
## minus_271 -99.944 17.046 -5.863 4.29e-08 ***
## minus_59 -60.553 8.927 -6.783 5.10e-10 ***
## minus_62 -20.145 7.376 -2.731 0.00729 **
## factor(econ)2 19.807 21.843 0.907 0.36637
## factor(econ)3 6.720 22.074 0.304 0.76135
## factor(econ)6 3.385 20.362 0.166 0.86824
## factor(sup)1 9.675 10.779 0.898 0.37126
## factor(sup)2 12.947 10.811 1.198 0.23349
## factor(job)1 18.243 10.487 1.740 0.08454 .
## factor(job)2 8.196 17.889 0.458 0.64767
## factor(job)3 24.576 10.675 2.302 0.02308 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.01 on 117 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.7214, Adjusted R-squared: 0.6762
## F-statistic: 15.95 on 19 and 117 DF, p-value: < 2.2e-16犯罪行為人之品行
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(prev), data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -49.24 -11.43 -4.18 7.82 129.32
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 76.180 2.466 30.890 < 2e-16 ***
## plus_47 2.186 3.814 0.573 0.567470
## plus_112 29.438 8.335 3.532 0.000555 ***
## minus_192 -20.991 6.030 -3.481 0.000661 ***
## minus_271 -18.365 21.293 -0.863 0.389834
## minus_59 -34.625 7.022 -4.931 2.23e-06 ***
## minus_62 -22.507 6.165 -3.651 0.000365 ***
## factor(prev)1 5.062 4.420 1.145 0.253993
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.02 on 144 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3243, Adjusted R-squared: 0.2915
## F-statistic: 9.874 on 7 and 144 DF, p-value: 4.982e-10既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(prev),
## data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -106.425 -9.921 0.204 12.204 82.825
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 155.7961 4.1908 37.175 < 2e-16 ***
## factor(art)2 -58.6215 5.3570 -10.943 < 2e-16 ***
## factor(art)3 -70.9212 17.1504 -4.135 6.48e-05 ***
## factor(art)5 -36.0000 40.3503 -0.892 0.374021
## plus_47 20.7464 5.8114 3.570 0.000509 ***
## plus_112 8.6930 8.3368 1.043 0.299102
## minus_192 0.2039 28.8381 0.007 0.994369
## minus_20 -25.2529 33.1636 -0.761 0.447825
## minus_23 -24.2568 17.7024 -1.370 0.173082
## minus_271 -106.5432 16.9860 -6.272 5.41e-09 ***
## minus_59 -64.6104 8.7077 -7.420 1.62e-11 ***
## minus_62 -18.3877 7.1361 -2.577 0.011146 *
## factor(prev)1 -6.1174 7.5967 -0.805 0.422201
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.53 on 124 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6937, Adjusted R-squared: 0.664
## F-statistic: 23.4 on 12 and 124 DF, p-value: < 2.2e-16犯罪行為人之智識程度
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(educ) + ment_ill, data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -58.697 -10.424 -4.280 8.492 126.660
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 55.937 14.951 3.741 0.000268 ***
## plus_47 1.234 3.941 0.313 0.754737
## plus_112 30.916 8.167 3.785 0.000228 ***
## minus_192 -27.503 6.873 -4.002 0.000102 ***
## minus_271 -23.658 20.801 -1.137 0.257373
## minus_59 -37.621 6.966 -5.401 2.82e-07 ***
## minus_62 -24.788 6.058 -4.092 7.24e-05 ***
## factor(educ)1 15.130 15.870 0.953 0.342046
## factor(educ)2 26.488 15.184 1.744 0.083305 .
## factor(educ)3 16.296 15.288 1.066 0.288311
## factor(educ)5 10.063 17.531 0.574 0.566879
## factor(educ)6 40.063 25.349 1.580 0.116290
## factor(educ)7 20.344 15.344 1.326 0.187096
## ment_ill 19.630 7.859 2.498 0.013668 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 20.47 on 138 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3857, Adjusted R-squared: 0.3278
## F-statistic: 6.665 on 13 and 138 DF, p-value: 8.767e-10既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(educ) +
## ment_ill, data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -113.296 -9.630 -0.831 15.987 86.183
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 158.101 20.480 7.720 4.17e-12 ***
## factor(art)2 -60.203 5.665 -10.628 < 2e-16 ***
## factor(art)3 -74.598 18.051 -4.133 6.73e-05 ***
## factor(art)5 -29.856 41.527 -0.719 0.47359
## plus_47 18.130 5.904 3.071 0.00265 **
## plus_112 10.869 8.654 1.256 0.21163
## minus_192 -3.178 29.547 -0.108 0.91453
## minus_20 -23.760 39.023 -0.609 0.54378
## minus_23 -25.461 18.086 -1.408 0.16183
## minus_271 -110.341 17.211 -6.411 3.10e-09 ***
## minus_59 -64.542 9.022 -7.154 7.69e-11 ***
## minus_62 -15.080 7.542 -1.999 0.04785 *
## factor(educ)1 -4.471 21.361 -0.209 0.83457
## factor(educ)2 1.077 21.199 0.051 0.95957
## factor(educ)3 -5.067 21.542 -0.235 0.81444
## factor(educ)4 4.214 26.357 0.160 0.87324
## factor(educ)5 -23.958 24.017 -0.998 0.32054
## factor(educ)7 1.064 20.861 0.051 0.95939
## ment_ill -8.412 11.830 -0.711 0.47846
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.69 on 118 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.7054, Adjusted R-squared: 0.6604
## F-statistic: 15.69 on 18 and 118 DF, p-value: < 2.2e-16犯罪行為人與被害人之關係
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(relation), data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -49.936 -11.515 -4.147 7.379 132.749
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 75.8814 2.8710 26.430 < 2e-16 ***
## plus_47 2.6848 3.8825 0.692 0.490376
## plus_112 31.3700 8.4116 3.729 0.000277 ***
## minus_192 -19.6592 6.0574 -3.245 0.001462 **
## minus_271 -28.7786 22.0222 -1.307 0.193393
## minus_59 -38.7794 7.2323 -5.362 3.26e-07 ***
## minus_62 -22.3666 6.1644 -3.628 0.000397 ***
## factor(relation)2 10.2124 6.1840 1.651 0.100861
## factor(relation)3 0.2653 3.6969 0.072 0.942889
## factor(relation)4 11.4338 21.3899 0.535 0.593802
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.03 on 142 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.3326, Adjusted R-squared: 0.2903
## F-statistic: 7.864 on 9 and 142 DF, p-value: 2.294e-09既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(relation),
## data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -110.559 -10.393 0.292 13.607 84.292
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 156.454 5.424 28.843 < 2e-16 ***
## factor(art)2 -58.685 5.454 -10.760 < 2e-16 ***
## factor(art)3 -71.857 17.236 -4.169 5.72e-05 ***
## factor(art)5 -36.090 41.891 -0.862 0.390624
## plus_47 20.166 5.788 3.484 0.000685 ***
## plus_112 8.234 8.840 0.932 0.353414
## minus_192 1.607 29.082 0.055 0.956032
## minus_20 -23.394 34.899 -0.670 0.503900
## minus_23 -24.622 18.001 -1.368 0.173869
## minus_271 -107.089 17.154 -6.243 6.37e-09 ***
## minus_59 -64.297 8.969 -7.169 6.16e-11 ***
## minus_62 -18.078 7.200 -2.511 0.013349 *
## factor(relation)2 -1.971 10.342 -0.191 0.849193
## factor(relation)3 -2.060 5.526 -0.373 0.709886
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.71 on 123 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6924, Adjusted R-squared: 0.6599
## F-statistic: 21.3 on 13 and 123 DF, p-value: < 2.2e-16犯罪所生之危險或損害
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + inj_all, data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -44.310 -10.609 -4.310 8.127 61.405
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 69.9697 2.1608 32.381 < 2e-16 ***
## plus_47 4.2499 3.2239 1.318 0.190
## plus_112 5.1779 7.7142 0.671 0.503
## minus_192 -21.1861 5.0893 -4.163 5.39e-05 ***
## minus_271 -20.5602 17.9640 -1.145 0.254
## minus_59 -29.7155 5.9283 -5.012 1.55e-06 ***
## minus_62 -21.0020 5.1886 -4.048 8.41e-05 ***
## inj_all 6.3406 0.8213 7.720 1.79e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 17.76 on 144 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.5178, Adjusted R-squared: 0.4943
## F-statistic: 22.09 on 7 and 144 DF, p-value: < 2.2e-16既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + death,
## data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -111.518 -10.639 -1.294 13.361 86.113
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 142.887 9.249 15.448 < 2e-16 ***
## factor(art)2 -60.752 5.549 -10.949 < 2e-16 ***
## factor(art)3 -71.892 17.014 -4.225 4.58e-05 ***
## factor(art)5 -36.000 40.107 -0.898 0.371140
## plus_47 20.879 5.735 3.640 0.000398 ***
## plus_112 10.891 8.397 1.297 0.197018
## minus_192 1.361 28.653 0.048 0.962191
## minus_20 -22.892 32.885 -0.696 0.487661
## minus_23 -23.491 17.588 -1.336 0.184120
## minus_271 -95.995 18.612 -5.158 9.60e-07 ***
## minus_59 -63.790 8.669 -7.358 2.24e-11 ***
## minus_62 -17.555 7.102 -2.472 0.014798 *
## death 11.752 7.988 1.471 0.143773
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.36 on 124 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.6974, Adjusted R-squared: 0.6681
## F-statistic: 23.81 on 12 and 124 DF, p-value: < 2.2e-16犯罪後之態度
未遂
##
## Call:
## lm(formula = sent_y ~ plus_47 + plus_112 + minus_192 + minus_271 +
## minus_59 + minus_62 + factor(att) + factor(recon), data = att)
##
## Residuals:
## Min 1Q Median 3Q Max
## -32.946 -10.502 -2.617 8.236 124.777
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 85.356 3.053 27.955 < 2e-16 ***
## plus_47 4.616 3.730 1.238 0.217936
## plus_112 29.868 8.303 3.597 0.000446 ***
## minus_192 -18.035 5.941 -3.036 0.002865 **
## minus_271 -26.096 20.291 -1.286 0.200551
## minus_59 -29.585 6.723 -4.400 2.14e-05 ***
## minus_62 -23.732 5.870 -4.043 8.70e-05 ***
## factor(att)1 -5.327 4.416 -1.206 0.229753
## factor(att)2 -10.703 4.781 -2.239 0.026777 *
## factor(att)3 -6.991 5.273 -1.326 0.187104
## factor(recon)1 -10.610 4.026 -2.636 0.009352 **
## factor(recon)2 -27.243 7.336 -3.714 0.000295 ***
## factor(recon)3 -3.876 4.410 -0.879 0.380958
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 19.73 on 139 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.4254, Adjusted R-squared: 0.3758
## F-statistic: 8.574 on 12 and 139 DF, p-value: 4.857e-12既遂
##
## Call:
## lm(formula = sent_y ~ factor(art) + plus_47 + plus_112 + minus_192 +
## minus_20 + minus_23 + minus_271 + minus_59 + minus_62 + factor(att) +
## factor(recon), data = acc)
##
## Residuals:
## Min 1Q Median 3Q Max
## -112.612 -9.979 0.000 12.974 78.843
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 159.779 5.730 27.885 < 2e-16 ***
## factor(art)2 -57.801 5.555 -10.405 < 2e-16 ***
## factor(art)3 -68.125 17.315 -3.935 0.000141 ***
## factor(art)5 -20.064 40.783 -0.492 0.623647
## plus_47 16.833 5.971 2.819 0.005642 **
## plus_112 10.019 8.425 1.189 0.236749
## minus_192 -1.087 29.043 -0.037 0.970210
## minus_20 -27.641 34.416 -0.803 0.423499
## minus_23 -32.605 18.521 -1.760 0.080907 .
## minus_271 -93.340 19.165 -4.870 3.46e-06 ***
## minus_59 -56.677 9.448 -5.999 2.20e-08 ***
## minus_62 -15.676 7.259 -2.159 0.032821 *
## factor(att)1 -2.692 6.577 -0.409 0.682994
## factor(att)2 -3.631 7.277 -0.499 0.618719
## factor(att)3 1.137 7.630 0.149 0.881749
## factor(recon)1 -15.936 7.538 -2.114 0.036600 *
## factor(recon)2 -19.023 14.259 -1.334 0.184721
## factor(recon)3 -0.822 6.870 -0.120 0.904955
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 28.34 on 119 degrees of freedom
## (22 observations deleted due to missingness)
## Multiple R-squared: 0.7099, Adjusted R-squared: 0.6685
## F-statistic: 17.13 on 17 and 119 DF, p-value: < 2.2e-16參考文獻
- 余麗貞（2010）。臺灣地區殺人案件量刑因素之研究。國立臺灣大學政治學研究所碩士論文。
- 蔡彩貞（2012）。殺人罪量刑之實證研究。國立臺灣大學碩士在職專班財務金融組碩士論文。
- 許旭聖（2015）。從我國殺人罪審判實務的量刑因子分析：論性別對科刑的影響。臺北市：司法院
- 陳玉書、林健陽、賴宏信、郭豫珍（2011）。殺人罪量刑準則之實證分析。中央警察大學犯罪防治學報，13，77-115。