# How to Use SPSS in Biomedical Data analysis

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How to Use SPSS in Biomedical Data analysis

SPSS: Statistical Package for Social Science

(2)服務單位 電話 (3)單位主管意見 (4)教研部主任意見 二、 (1)統計諮詢 (2)研究諮詢 (3)論文review (4)其他 教研部

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Repeated measures ANOVA Logistic regression Survival analysis Validation of questionnaire How to design a questionnaire How to create a data base for follow-up study

Characteristics of Biomedical Data
1. Variables and Constant 2. Classification of variables： 1) Independent variables and Dependent variables 2) Continuous variables and Discrete variables a) Continuous variables: Ht., Wt, Time, IQ, Anxiety Score, BP ↑ ↑ ↑ ↑ ↑ cm b) Discrete variables: Type of treatment, Survival status, Location of cancer, Morphology, and Genotype

3)Nominal variables, Ordinal variables, Interval variables and Ratio variables
a)Nominal variables: ID No., Type of treatment, sex, color, name, etc. b)Ordinal variables: rank, grade, likert scale, etc. *if a > b and b> c then a> c, but a-b≠b-c Grade A > Grade B > Grade C, but Grade A – Grade B ≠ Grade B –Grade C c)Interval variables: temperature, lightness, etc. *variable with equal unit *variable without absolute zero *if a >b >c then a-b = b-c *if 39℃ > 37 ℃>35 ℃ then 39 ℃-37 ℃= 37 ℃- 35 ℃

d)Ratio variables: Ht., Wt., etc.
*variable with equal unit *variable with absolute zero 120cm: from 0cm to 120cm 37℃ : from 0℃ to 37℃ from 20℃ to 37℃ from -5℃ to 37℃ from -50℃ to 37℃ *if a＞b＞c then a-b = b-c *if a＞b＞c then a/b = b/c if cm＞60cm＞30cm then 120cm/60cm = 60cm/30cm

The Common Statistical Methods (1)
Independent Variable Dependent Variable Statistical Method Categorical variable Categorical v X2 test Categorical v Continuous v t test or ANOVA Categorical v Ordinal v Mann-Whitney U test Kruskal-Wallis one-way ANOVA Continuous v Continuous v Regression or Pearson correlation Ordinal v Ordinal v Spearman correlation

The Common Statistical Methods(2) Independent Variable Dependent Variable Statistical Method More than 1 conti v. Continuous v Multiple regression More than 1 conti v. and (or) Binomial or multinomial v Logistic regression more than 1 cate v.

The Common Statistical Methods(3) Independent Variable Dependent Variable Statistical Method Categorical v Time Log rank test, Log rank test, Breslow test, Tarone-Ware test More than 1cate v Cox’s regression and (or) Time (Proportional more than 1conti v Hazard Model)

Chi-square test (Pearson)
df = (R-1)(C-1) 例：問卷調查醫生、藥劑師、與護士，問卷回收情形如下，請問回收率是否依專業而不同？

df= (R-1)(C-1)=(2-1)(3-1)=2 *X2.95(2) = 5.991

Fisher’s Exact Test *to compare two proportions for the nominal variables 訪問6名男生和7名女生喜不喜歡跳傘運動，結果如下表(B)所示，亦即回答喜歡者男生有4名，女生有1名。問男生是否較女生喜歡跳傘運動？ (A) 極端情形 (B) 性 別 性 別 跳 傘 跳 傘

df = N1+N2-2

1.該心理學家認為是否打RNA對老鼠學習有所影響，統計假設應寫為：
H0:μx1=μx2 H1:μx1≠μx2 2.母群的σ2x1和σ2x2均為未知，必須使用不偏估計值s2P，而且因為 σ2x1=σ2x2=σ2的假設可以符合。 3.如果犯第一類型錯誤便是很嚴重的，因之，實驗者決定使用.01顯著水 準。又因為 H1:μx1≠μx2，所以查附錄表D，得t1-.005( )=2.819。 倘實際計算所得t值大於2.819，則應拒絕 H0:μx1=μx2 。 4.實際計算所得t=1.78，小於查表t值2.819，故H0應予接受。

or matched samples)， Paired t-test 如：a.同一組人經實驗處理(吃降血壓藥)後，做前測血壓與後 測血壓平均值之比較。 b.教研部在CQI實行前後各實驗室平均論文篇數的比較。 c. 高榮在CQI實行前後各科健保給付剔退案平均數之比較。

…… [公式 1] ，即這些差值的平均數等於前後兩個平均數之差 是這些差值的標準差； 便是假定我們重複抽取無限多對 還有， 得無限多 時，這些 的分配的標準誤。 故： df = N-1

1.研究者主張創造力訓練課程可以提高創造力，亦即後測的

[公式 1]

3.研究者願意冒犯第一類型錯誤的機率為.01，亦即α= .01。

Using SPSS to Evaluate Data for Normality
Luo-Ping Ger Kaohsiung Veterans General Hospital Department of Education and Research

The Common Statistical Methods (1)
Independent Variable Dependent Variable Statistical Method Categorical variable Categorical v X2 test Categorical v Continuous v t test or ANOVA Categorical v Ordinal v Mann-Whitney U test Kruskal-Wallis one-way ANOVA Continuous v Continuous v Regression or Pearson correlation Ordinal v Ordinal v Spearman correlation

Post-hoc analysis:

The Common Statistical Methods (1)
Independent Variable Dependent Variable Statistical Method Categorical variable Categorical v X2 test Categorical v Continuous v t test or ANOVA Categorical v Ordinal v Mann-Whitney U test Kruskal-Wallis one-way ANOVA Continuous v Continuous v Regression or Pearson correlation Ordinal v Ordinal v Spearman correlation

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