当代对组织、策略与管理的研究，大部份依据定量研究方法。本课程将介绍一些最常使用的定量方法，包括对数转换值／机率转换值模型、计算模型、事件历史模型，并将各技术做跨区域整合。

这是关于研究过程的一门课程。我明确的目标是在帮助你理解理论、数据和统计方法之间的关系。这不是一门统计学理论课程；虽然会明确地依据统计过程订定假说，但并不会花很多时间在推导可能的函数…等等，而是如何使用统计方法来回答研究问题。我们会花相当多的时间在思考如何将理论转化为可验证的假说，以及如何最有效地验证这样的假说。我们将藉由讨论组织研究领域中的主要期刊，并让你使用数据和估计模型加以进行。这些技巧中我主要目标是帮助你能轻易地使用统计方法提出与解决研究问题，并且发展评估他人研究的关键性技能，这样就可以将这些技能应用于自己的研究上。

形式与要求

本课程之架构（大致上）为一周的理论授课与隔周的理论应用相互交替。我们将使用以下两种方式:

• 首先，讨论使用特定方法的报告（从网络和其他地方取得），为了评估这些数据与方法对于研究问题来说是否得宜。
  
  
• 其次，我会要求学生处理数据与估计模型（使用STATAR），写下结果并阐明原因，然后（偶尔）在课堂中报告。

数据作业中之文句须得宜。最重要的是这些作业都没有特定答案。我不会指定你该用什么相依变数、该解释什么…等等。这样的部份目的是要让你练习如何使用数据、估计模型和使答案合理化。利用课程15.347所学，你要规划出数据的概念性模型和统计模型。这门课较大的限制是你只能使用当周课堂中讨论的方法（例如：计算模型）。我都已经将适当的数据资料设定好，不过你也可以使用自己取得的数据。

每次“应用”课的开始都要交一份分析结果概要，本文最多两页，加上图表，并根据推衍出的概念性模型讨论其结果。这些作业最多可由两人一组完成。我每周会请两或三组提出他们的作品结果，并在课堂中讨论。

评分分配标准如下：

软件

若你没用过STATAR，我希望你在开课的前几周作以下事项:

1. 安装软件（比方在计算机实验室），以便让你知道如何运作。
   
   
2. 2. 至少先浏览使用手册，特别是阅读“开始使用STATA®”。

网络上也可取得资源，例如：UCLA提供的STATA®启动工具。

教科书

Alrich, John H.和Forrest D. Nelson着，《线性机率, 对数转换值／机率转换值模型》，Newbury Park,CA:Sage出版，1984，ISBN: 0803921330.

Singer, Judith D.和John B. Willett着，《应用纵向数据分析：模型改变与事件产生》，纽约：牛津大学出版社，2003，ISBN: 0195152964.

A large proportion of contemporary research on organizations, strategy and management relies on quantitative research methods. This course is designed to provide an introduction to some of the most commonly used quantitative techniques, including logit/probit models, count models, event history models, and pooled cross-section techniques.

This is a course about the research process. My explicit goal is to help you understand the relationship between theory, data and statistical methods. In that sense this is not a course in statistical theory; we will not spend a lot of time deriving likelihood functions, etc., although we will be explicit about the assumptions underlying the statistical procedures. Instead, this is a course in how to use statistical techniques to answer research questions. We will spend considerable time thinking about how theoretical insights can be translated into testable propositions, and how those propositions are best tested. We will do this through discussions of published research from leading journals in organizational research, and by having you work with data and estimate models. My primary goal in these skills is to help you increase your comfort with using statistical methods to ask and answer research questions, and to develop critical skills in evaluating others' research, such that you might apply those skills to your own.

Format and Requirements

The structure of the course involves (roughly) alternating lectures on the principles associated with a particular method in one week, followed the next week by the application of those models. We will pursue two types of application:

• First, we will discuss working papers (found on the Internet and elsewhere) that use the particular methods in question, with an eye toward assessing whether the data and methods are appropriate for the research question.
  
  
• Second, I will ask students to work with data to estimate models (in STATA®), write up an interpretation of the results, and then (occasionally) present the results in class.

Some words about the data assignments are in order. Most importantly, these assignments are deliberately open-ended. I will not specify what the dependent variable should be, what you are trying to explain, etc. Part of the goal of these exercises is to give you practice with working with data, estimating models and making sense of the results. In the language of 15.347, I want you to formulate a conceptual model of the data as well as a statistical model. The major constraint is that you apply the method discussed during that week's class (e.g., count models). I will make appropriate datasets available for this purpose, but you are also allowed to use your own data sources.

At the beginning of class in each "Application" week, I ask that you hand in a brief summary of the results of your analysis. This summary should be a maximum of two pages of text, plus any tables and figures, and should discuss the results in light of the conceptual model you have developed. These assignments may be done in groups of up to two people. I will ask two or three groups each week to present the results of their work, so that we may discuss them as a class.

The grading is broken down as follows:

Software

If you have not worked with STATA® before, I encourage you to do things during the first few weeks of class:

1. Get yourself set up (e.g., in the computer lab) so that you know how to get it going and
   
   
2. At least look through some of the manuals. It can be particularly helpful to look at "Getting Started with STATA®."

There are also resources available on the Internet, e.g., the STATA® Starter Kit provided through UCLA .

Texts

Aldrich, John H., and Forrest D. Nelson. Linear Probability, Logit and Probit Models. Newbury Park, CA: Sage, 1984. ISBN: 0803921330.

Singer, Judith D., and John B. Willett. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. New York: Oxford University Press, 2003. ISBN: 0195152964.