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I. Introduction

研究方法學：統計學、流行病學Methodology

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Biostatistics

研究與生活：洗碗工的故事 背景與鬥志

羅炳輝，世新電影編導畢，塑膠廠工人，與同學的偶然深談對飯店產生莫大興趣， 1981 年到來來飯店，從洗碗幹起。早、晚、大夜班輪著洗碗，一班洗個一、二千個碗盤，洗到腰痠背痛，手皮磨破

這種年齡幹這種工作，一般人很難提起鬥志。那年他 28 歲，這人還有前途嗎 ? 研究與升遷

他抽空研究洗碗劑、碗盤材質、器皿擺放，不僅要擺得整齊美觀，還兼具取放方便，飯店也購置洗碗機，但很少人用，不是速度太慢就是洗不乾淨，不如用手洗，但他卻開始研究水溫、水壓、藥劑，讓機器能發揮最大效用

他邊洗邊研究了兩年，飯店升他當管理員，四年後再調升為副理。 長期的鑽研，他成了洗碗專家，還對各種高級器皿的材質、釉質及適合的藥劑，瞭

若指掌。除了研究飯店本身的器皿，他還蒐集資料，對各種杯盤器皿如數家珍。 現職與著作

2000 擔任天祥晶華度假酒店新任總經理 著作：餐飲管理──器皿管理實務

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Biostatistics

研究與生活：賣飯團的故事 背景與鬥志

余政隆， 55 年次，高職電子科畢，退伍後找不到工作，家中有閒置不用的飯糰器具，便開始路邊擺攤的工作生涯。

這種年齡幹這種工作，一般人很難提起鬥志。這人還有前途嗎 ? 研究與發跡

「為什麼西式早餐店一家一家開，本土的糯米飯糰卻做不起來？」他越想越不服氣。一邊開書局一邊蒐集資料，「有一天我要把台灣米食發揚光大」。

余政隆花了兩年，每天用八個快速爐煮飯，研究什麼樣的米、火侯怎麼控制、煮出來的飯糰最好吃，搭配什麼樣的材料，消費者才會百吃不厭，吃了不脹氣。「那兩年，我每天望著飯桶發呆，連晚上睡覺，做夢都夢到煮飯，到處找米。」

親友也覺得「阿隆」怪怪的，因為他不僅滿口米食經，每次出國旅遊時，人家忙著參觀名勝、買特產，只有阿隆四處找當地米，還自備電鍋煮起來。有一次入關時，余政隆從國外買的十幾種米全被沒收，全家臉都綠了。

事業現況 目前全國已有兩、三百家的店面或路邊攤，採用他的「傳香飯糰」，亦即每天有數萬

人一起享用他研發的創意飯糰，因此他自稱為「飯糰的魔法師」，是帶給人們幸福的人。

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Biostatistics

研究與生活的態度你有多久沒有問為什麼？

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Biostatistics

Introduction

The Role and Scope of Biostatistics & Epidemiology: Scope Roles of Statistics

VariableData measurement

Overview of the text book Examples

Disease Natural History Disease Prevention framework Research and causal inference

Textbook: Basic & Clinical Biostatistics, Dawson, 4th edition, 2004

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Biostatistics

Role of Statistics

To be a good citizenStatistical thinking would one day be as

necessary for good citizenship as the ability to read and write. H.G Wells, 1866-1946 English novelist, journalist, sociologist, and historian

To have a good decision-making processesNew drugs: clinical trialSeat belt or air bag: mortality in car accidentMastectomy: breast cancer

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Biostatistics

Biostatistics: objective

Develop sound judgment about data applicable to clinical care

Read the medical literature critically and apply the results of medical studies confidently to patient care

Interpret commonly used vital statistics and epidemiologic information for patient care and prevention of disease

Develop familiarity with statistical software and interpret the computer output

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Biostatistics

The study of statistics

Telling a story with numbers:Exploring the collection, organization, analysis,

and interpretation of numerical data. Applied field:

Business, marketing, economics, politics, agriculture, education, psychology, sociology, anthropology, biology, Public Health….

Biostatistics: focusing on biological and health science

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Biostatistics

Variables and study question Outcome (dependent) variable: Y

Systolic blood pressureAngina pectoris:

0:no; 1:mild; 2:severe

Explanatory (independent) variable: X, Treatment

1:new drug; 0: standard drugBMI

Causality and correlationY=a+b1X1+b2X2+b3X3+b4X4+b5X5… covariate, confounder

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Biostatistics

Fisher British statistician and geneticist

pioneering the application of statistical procedures to the design of scientific experiments.

Characteristics a sickly, poor-eyesighted child The teacher used no paper/pencil to

teach him Mathematicians take years to prove

his formulas

Persistence Calculation of ANOVA tables takes F

isher 8 months, 8h/D to finish!!

Reference: The lady tasting tea, Salsburg, 2001 「統計，改變了世界」天下， 2001

Sir Ronald Aylmer Fisher 1890-1962

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Biostatistics

Overview of the Text

Descriptive statistics: Chapter 1: Introduction

Extraction of important information from data not precluded by the variability among them

Data often exhibit regularity

Chapter 2: Study Designs in Medical ResearchChapter 3: summarizing data & Presenting data

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Biostatistics

Overview of the Text, cont.

probability & distribution properties of sample mean Chapter 4

Central limit theorem

Research questions about One group Chapter 5

confidence interval & hypothesis testing Sample → categorical X; mean → numerical Y

Research questions about Two separate or independent group Chapter 6

Research questions about Means in Three or more group Chapter 7

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Biostatistics

Overview of the Text, cont.

Research questions about Relationships among variables Chapter 8

Analyzing Research questions about survival Chapter 9

Statistical Methods for Multiple Variables Chapter 10

Survey research Chapter 11

Methods of evidence-based medicine and decision analysis Chapter 12

Reading the medical literature Chapter 13

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Biostatistics

Example: Ab structure

variability and regularity Wu TT, Kabat EA An analysis of the sequences of the variabl

e regions of Bence Jones proteins and myeloma light chains and their implications for antibody complementarity.J Exp Med. 1970 Aug 1;132(2):211-50.

Accurate prediction of Ab structure more than 10 years before the emergence of relevant technology

Definition of variability:(No. of a.a. found) / freq of the most common a.a.

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Biostatistics

統計：科學、迷信與事實真相棒球：最多統計數字的運動

科學：打擊率、自責分、左投克左打、第一棒排左打… .等

迷信：貝比魯斯魔咒、山羊魔咒、阿扁魔咒、小馬哥神咒連勝的隊伍球員不換內褲

車禍：高度不確定的事件台灣每年死亡人數：約三到五千人為何如此穩定出現 ?個體不確定與集體的確定

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Biostatistics

因果關係判定的基準 必要基準：

時序性 (temporality) 次必要基準：

一致性 (consistency) 機會無法解釋沒有其他干擾性的解釋因素 合理性 (coherence) 相關強度 (strength of association)相關的特定程度 (specificity of association) 生物性漸增趨勢 (biological gradient)或劑量反應關係 生物學上的贊同性 (biological plausibility)

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Biostatistics

這種研究是笑話嗎 ?!　 研究題目：

Effects of remote, retroactive intercessory prayer on outcomes in patients with bloodstream infection: randomised controlled trial BMJ 2001;323:1450-1451 ( 22-29 December )

研究設計： Objective: To determine whether intercessory prayer has an effect Design: Double blind, parallel group, randomised controlled trial Subjects: All 3393 adult patients whose bloodstream infection was detected a

t the hospital in 1990-6 Intervention: In July 2000 patients were randomised to a control group and a

n intervention group. Main outcome measures: Mortality in hospital, length of stay in hospital, and

duration of fever. Results: Mortality was 28.1% (475/1691) in the intervention group and 30.2%

(514/1702) in the control group (P for difference=0.4). Length of stay in hospital and duration of fever were significantly shorter in the intervention group than in the control group (P=0.01 and P=0.04, respectively).

Conclusions: Remote, retroactive intercessory prayer said for a group is associated with a shorter stay in hospital and shorter duration of fever in patients with a bloodstream infection and should be considered for use in clinical practice.

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Biostatistics

研究文獻舉例 : 描述統計表

Effects of remote, retroactive intercessory prayer on outcomes in patients with bloodstream infection: randomised controlled trial BMJ 2001;323:1450-1451 ( 22-29 December )

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Biostatistics

研究文獻舉例 : 分析統計表

BMJ 2001;323:1450-1451 ( 22-29 December )

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Biostatistics

Variables

VariablesA characteristic of interest in a study With different VALUE for different measurement u

nitsGender: male, femaleBlood pressure: 130 mHg

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Biostatistics

Variables and study question Outcome (dependent) variable: Y

Systolic blood pressureAngina pectoris:

0:no; 1:mild; 2:severe

Explanatory (independent) variable: X, Treatment

1:new drug; 0: standard drugBMI

Causality and correlationY=a+b1X1+b2X2+b3X3+b4X4+b5X5… covariate, confounder

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Biostatistics

Measurement

All science is measurementHelmholts, German physiologist

Good measurementGreat science breakthrough is always about mea

surement improvementTo do everything well is to measure it well

DefinitionDefinition of variablesDefinition of Denominator and Numerator

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Biostatistics

Types of data measurements

Nominal scale : ( =, ≠ ) Race, gender, etc Also called categorical data, qualitative scale

Ordinal scale : ( =, ≠, >, < ) Your satisfaction score about YMU

Numerical scale : Interval scale (=, ≠, >, <, +, )

Temperature: zero is NOT NOTHING in quantity in measuring

Ratio scale ( =, ≠, >, <, +, , , )Weight: zero is nothing in quantity in measuring

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Biostatistics

Types of Numerical Data: Nominal Data: ( 數值大小不重要 )

Sex: (dichotomous, binary data) male=1; female=0

Blood type: O=1; A=2; B=3; AB=4

Ordinal Data: (順序重要，數值大小仍不重要 ) Level of severity:

fatal=1; sever=2; moderate=3; minor=4 Oncology Group’s Classification of Pt. Performance status

Status Definition

0 Fully active

1 Restricted in physically strenuous activity

2 Ambulatory and capable of all-self care

3 Capable of only limited self-care

4 Completed disabled

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Biostatistics

Types of Numerical data, cont.

Ranked Data: (依數值大小排序，但數值大小仍不重要 ) Ten leading causes of death, USA, 1992

1. Heart diseases; 2. Neoplasm; 3. CVD; 4. COPD….,

Discrete Data: (順序與數值大小兩者皆重要 ) Data Values are specified: Counts or integers:

2004 年 9月台北的車禍意外數 Discrete data 的運算 : 結果不見得還是 discrete data

Continuous Data Data values not specified Transforming into discrete, ordinal, or dichotomous data

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Biostatistics

Data structure

ID Y1 Y2 X1 X2 … …

1 110 1 1 20

2 140 1 1 25

3 124 2 0 30

4 110 0 0 21

5 100 2 1 19

6 95 0 1 23

7 90 1 0 21

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Biostatistics

Types of data: BMI as examples

Body mass index, BMI as a numerical scale=[WT in kg/(height in M)2]

BMI as a ordinal scale20.5, 27, 34….

Obesity as a categorized BMI:Overweight: 27<BMI<30Obesity: BMI>30

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Biostatistics

Between measurement scales

Definition of mountain A prominence of 1000 fe

et, by Royal Geographical Society

An interesting movie山丘上的情人 The Englishman who we

nt up a hill but came down a mountain

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Biostatistics

Examples: the meaning of number

Person killed by handguns, 1979 48 in Japan, 34 in Switzerland, 52 in Canada, 58 in Israel, 2

1 in Sweden, 42 in Germany, 8 in England and 10,728 in US

No. of abortion for every 100 births 120 in Soviet Union, 20 in GB, 40 in US Access to contraception

Information and conviction Guns don’t kill people, people do.

討論：上述兩個例子的數據，有何不同 ? Denominator and numerator

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Biostatistics

Home Work準備教科書與 NCSS軟體

教科書、筆記型電腦下下週準備完成

基本觀念： 提出問題：

請提出一個您感興趣的研究問題假說定義該問題的因變項與果變項

如何測量、測量尺度是什麼下下週上課隨機抽問

將連續尺度轉成不連續或序位尺度時有何優缺點 ? (2-3)