心理測驗SPSS上機:信度分析
資料輸入
Data輸入頁
變項定義頁
Reliability Analysis
本次課題包含:
※如何進行各種信度分析
1. 再測信度(Test-Retest Reliability)
2. 複本信度(Alternate-form Reliability)
3. 折半信度(Split-half Reliability)
4. 內部一致性(Internal Consistency Coefficient)【計算α係數】
5. KR 20
【1】 再測信度(Test-Retest Reliability)
步驟一 按【Analyze】→【Correlate】→【Bivariate…】
步驟二 會出現下面的對話框,將左邊兩變項選入右邊「Variables」內,在「Correlation Coefficients」方盒內選取「□Pearson」;在「Test of Significance」方盒內選取「□Two-tailed」;勾選最下面的「□Flag significant correlations」,之後按鍵。
補充 若想呈現平均及標準差則可在按鍵前按進入下個對話框,在Statistics的方盒內選取「□Means and standard deviations」,按繼續。
Correlations
紙筆計算結果:
Person | A | B | C | D | E | F | G | H | I | J | σ | |
Oct | 18 | 16 | 5 | 13 | 15 | 16 | 12 | 5 | 8 | 10 | 11.8 | 4.4226 |
Apr | 18 | 18 | 6 | 16 | 17 | 16 | 14 | 5 | 7 | 11 | 12.8 | 4.8744 |
X1 X2 | 324 | 288 | 30 | 208 | 255 | 256 | 168 | 25 | 56 | 110 | ||
N=10
【2】 複本信度(Alternate-form Reliability)
做法與再測信度相同,請參照。
Correlations
紙筆計算結果:
Person | A | B | C | D | E | F | G | H | I | J | σ | |
Form A | 16 | 12 | 14 | 10 | 9 | 11 | 13 | 9 | 16 | 12 | 12.2 | 2.4413 |
Form B | 15 | 12 | 15 | 10 | 10 | 12 | 14 | 9 | 16 | 13 | 12.6 | 2.289 |
XA XB | 240 | 144 | 210 | 100 | 90 | 132 | 182 | 81 | 256 | 156 | ΣXAXB=1591 | |
N=10
【3】
步驟一 輸入資料
步驟二 轉換資料為數字
按【Transform】→【Recode】→【Into Same Variables…】
出現下面的對話框後將左邊方格內item1~item6選至右邊String Variables內後點選鍵
出現下列對話框後,將”N”定義為”0”,將”Y”定義為”1”後按鍵
之後便會將資料轉換成下面的數字
步驟三 將string的屬性改為numeric
步驟四 計算奇數題與偶數題的和
按【Transform】→【Compute…】即出現下面的對話框
(此為奇數題的範例,偶數題亦然)
結束後便會在spss Data Editor對話框中出現奇數題和偶數題的和
步驟四 執行Bivariate
Correlations
紙筆計算結果
Ⅰ. 計算兩個”半測驗”的相關
Student | Joe | Sam | Sue | Peg | Gil | σ | |
Odds | 2 | 1 | 2 | 1 | 1 | 1.4 | .4899 |
Evens | 3 | 2 | 3 | 1 | 2 | 2.2 | .7483 |
X1X2 | 6 | 2 | 6 | 1 | 2 | X1X2 =17 | |
N=5
Ⅱ 校正相關係數為折半信度
Spearmen-Brown prophesy formula 史比校正公式 (當兩個半測驗變異數相等時使用)
Guttman prophesy formula 哥德曼校正公式 (當兩個半測驗變異數不等時使用)
*折半信度* 折半信度也可直接使用SPSS計算
步驟一 輸入資料
步驟二 按【Analyze】→【Scale】→【Reliability Analysis】將左邊方格內的變項依所需次序分前後半選入右邊items的方格內,在左下角的Model框中選取Split-half後按鍵,再按。
Reliability
****** Method 1 (space saver) will be used for this analysis ******
R E L I A B I L I T Y A N A L Y S I S - S C A L E (S P L I T)
Reliability Coefficients
N of Cases = 5.0 N of Items = 6
Correlation between forms = .8729 Equal-length Spearman-Brown = .9321
Guttman Split-half = .8889 Unequal-length Spearman-Brown = .9321
3 Items in part 1 3 Items in part 2
Alpha for part 1 = -2.5000 Alpha for part 2 = .0000
標準的折半信度算法:先求各題的難度,再依難度加以排序,再施行上述的方法
透過平均值可看出其難度 平均高的難度低 平均低的難度高 排序由難度低到高2 6 1 4 5 3,在丟入變項時依單偶分為:2 1 5、6 4 3兩組,排列數據時前後排列。 | |
Correlations
Correlations
****** Method 1 (space saver) will be used for this analysis ******
R E L I A B I L I T Y A N A L Y S I S - S C A L E (S P L I T)
Reliability Coefficients
N of Cases = 5.0 N of Items = 6
Correlation between forms = .0000 Equal-length Spearman-Brown = .0000
Guttman Split-half = .0000 Unequal-length Spearman-Brown = .0000
>Note # 11999
>The correlation between forms (halves) of the test is negative. This
>violates reliability model assumptions. Statistics which are functions of
>this value may have estimates outside theoretically possible ranges.
3 Items in part 1 3 Items in part 2
Alpha for part 1 = -.9000 Alpha for part 2 = .6923
【4】 內部一致性(Internal Consistency Coefficient)【計算α係數】
步驟一 輸入資料
步驟二 按【Analyze】→【Scale】→【Reliability Analysis】
將左邊方格內的變項全選入右邊items的方格內,在左下角的Model框中選取Alpha後按鍵。
步驟三 出現下列對話框候選取下列勾選處,後按鍵
按。
Reliability
****** Method 2 (covariance matrix) will be used for this analysis ******
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Correlation Matrix
ITEM_1 ITEM_2 ITEM_3 ITEM_4 ITEM_5
ITEM_1 1.0000
ITEM_2 .2970 1.0000
ITEM_3 .7647 .5941 1.0000
ITEM_4 .6860 .4330 .8575 1.0000
ITEM_5 .1588 .8018 .4763 .4629 1.0000
N of Cases = 6.0
Item-total Statistics
Scale Scale Corrected
Mean Variance Item- Squared Alpha
if Item if Item Total Multiple if Item
Deleted Deleted Correlation Correlation Deleted
ITEM_1 13.0000 6.4000 .5251 .6471 .8472
ITEM_2 13.1667 5.3667 .6757 .7500 .8116
ITEM_3 12.3333 5.4667 .8333 .8588 .7642
ITEM_4 13.5000 6.7000 .7481 .7857 .8093
ITEM_5 12.6667 5.8667 .5922 .7143 .8333
Reliability Coefficients 5 items
Alpha = .8457 Standardized item alpha = .8609
紙筆計算結果
Question | 1 | 2 | 3 | 4 | 5 | Total Score |
Joe | 3 | 4 | 4 | 3 | 5 | 19 |
Sam | 4 | 3 | 4 | 3 | 3 | 17 |
Sue | 2 | 3 | 3 | 2 | 3 | 13 |
Peg | 4 | 4 | 5 | 3 | 4 | 20 |
Gil | 3 | 2 | 4 | 3 | 3 | 15 |
Dot | 3 | 2 | 3 | 2 | 3 | 13 |
σi2 = | .4722 | .6667 | .4722 | .2222 | .5833 | |
【5】 KR20
步驟一 轉換資料Y正確為1,N不正確為0
步驟二 與題四求內部ㄧ致性的步驟相同
Reliability
****** Method 2 (covariance matrix) will be used for this analysis ******
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Correlation Matrix
ITEM_1 | ITEM_2 | ITEM_3 | ITEM_4 | ITEM_5 | ITEM_6 | |
ITEM_1 | 1.0000 | |||||
ITEM_2 | -.6667 | 1.0000 | ||||
ITEM_3 | .4082 | .4082 | 1.0000 | |||
ITEM_4 | 1.0000 | -.6667 | .4082 | 1.0000 | ||
ITEM_5 | -.6124 | .4082 | -.2500 | -.6124 | 1.0000 | |
ITEM_6 | .1667 | .1667 | .4082 | .1667 | .4082 | 1.0000 |
* * * Warning * * * Determinant of matrix is close to zero: 8.426E-36
Statistics based on inverse matrix for scale ALPHA
are meaningless and printed as .
N of Cases = 5.0
Item-total Statistics
Scale Scale Corrected
Mean Variance Item- Squared Alpha
if Item if Item Total Multiple if Item
Deleted Deleted Correlation Correlation Deleted
ITEM_1 2.2000 1.7000 .1400 . .2941
ITEM_2 2.2000 2.2000 -.1846 . .5114
ITEM_3 2.6000 1.3000 .6864 . -.0962
ITEM_4 2.2000 1.7000 .1400 . .2941
ITEM_5 2.6000 2.3000 -.2212 . .4891
ITEM_6 2.2000 1.2000 .5833 . -.1042
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Reliability Coefficients 6 items
Alpha = .3273 Standardized item alpha = .3307
紙筆計算結果
Question | 1 | 2 | 3 | 4 | 5 | 6 | Total Score |
A | Y | Y | Y | Y | N | Y | 5 |
B | Y | N | N | Y | N | Y | 3 |
C | Y | N | N | Y | N | N | 2 |
D | N | Y | N | N | N | N | 1 |
E | N | Y | N | N | Y | Y | 3 |
Pi | .6 | .6 | .2 | .6 | .2 | .6 | |
qi | .4 | .4 | .8 | .4 | .8 | .4 | |
(p)(q) | .24 | .24 | .16 | .24 | .16 | .24 | |
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