こんなこともできる!「JMP 19」の新機能 ~ その3. 新しい Col () 関数とその利用例 ~
The latest release of JMP Clinical makes it the most sophisticated visualization and analysis tool for clinical trials the market. It has as much to do with our teams that build the software as it does its amazing functionality. Building on the powerful functionality of JMP Pro, JMP has delivered a solution that addresses the needs of a wide audience, including safety surveillance teams, medical m...
If you’re looking to make your data stories and presentations shine, forget static images and boring slides. JMP Public is a high-impact platform that showcases the dynamic, interactive power of JMP visualizations. Here are a few best practices to follow when posting: Enhance post interactivity and engagement If possible, share a report that will be interactive in JMP Public, such as a visuali...
In many ways, movies can catalog the history of your life, just as your books, music collection, concert tickets, or comics might. There is a story there of what your interests were at the time, who you saw them with, and what they meant to you. I thought it would be an interesting trip down memory lane to gather up these tickets, enter them into JMP, and explore the data. Plus, with paper tickets...
When two variables are related, the natural next question is “why?” Mediation analysis helps answer that by testing whether a third variable, the mediator, explains how the predictor influences the outcome. It moves us from “X is related to Y” to “X affects Y by changing M.” For example, in education research, we might find that students who feel a strong sense of belonging are more interested in ...
最新バージョン「JMP 19」では、「二変量の関係」プラットフォームの「一元配置分析」(Yに連続尺度、Xに名義・順序尺度を指定)のレポートにおいて、「Games-Howell検定」による平均の比較を行うオプションが追加されました。 ----------------------------------------------------------------------------------------------------------------- Games-Howell検定(JMPのホバーヘルプの説明より) すべてのペアの平均を比較する検定であり、また「各グループの誤差分散がすべて等しい」と仮定できない状況に対処した検定である。 -----------------------------------------------------------------------...
ついに、新しいバージョン「JMP 19」がリリースされました! もちろん「JMP 19」ではさまざまな機能が追加されています。主な新機能やアピールポイントについては、別のブログポストで紹介されています(原文は英語)。 そこで私の方では、あまり大々的にアピールはされていないけども、ユーザにとって便利で有用だと思える機能を数回にわたり紹介していきます。 第1回となる今回は、消費者調査や満足度調査などで役立つ「多重応答」についての新機能を取り上げます。JMP 19では「多重応答」列を用いたフィルタリング、集計表の作成ができるようになりました。 多重応答とJMPの設定 多重応答とは、アンケート調査などにおける「複数回答」(当てはめるものをすべて、あるいはいくつか選択して回答する形式)に対応するJMPの尺度やプロパティです。 下図は、ある企業研修のアンケートの回答をまとめた...
Ken Bollen: The many advantages of structural equation models
本記事では、医薬品開発における精度評価で用いられる「室内再現精度(Intermediate precision)」と「併行精度(Repeatability)」をJMPを用いて算出する方法を例題に沿って説明します。 この記事を書くきっかけとなったのは、最近公開した小野薬品工業株式会社様のユーザー事例 です。この事例の中では、室内再現精度や併行精度の評価方法として、制限付き最尤法(REML)を用いて分散成分を推定するといったコメントがあります。 この事例をご覧になったユーザーから「この方法を詳しく説明してほしい」という要望をいただいたため、本記事を執筆することにしました。 室内再現精度と併行精度とは ここでいう「精度」とは、同一試料(検体)を複数回測定した際の測定値間のばらつきを評価することを指します。 医薬品のガイドラインである「ICH-Q2 分析法バリデーション」では、次...
JMP Marketplace is an online platform to help you extend JMP as your needs evolve. Like other app stores, JMP Marketplace offers a curated selection of fully tested applications, add-ins, data connectors, and other extensions that enhance and expand JMP’s powerful capabilities. Watch a demo of the Marketplace here.
When treatment is binary, the Causal Treatment personality in JMP enables you to choose between four estimation techniques: inverse probability weighting with ratio adjustment (IPWR), regression adjustment (REGADJ), augmented inverse probability weighting (AIPW), and propensity score matching. You may be comfortable with one of these estimation methods, or you may have no idea where to begin. Alon...
Randomized controlled trials (RCTs) and other carefully designed statistical experiments are the gold standard for answering questions about cause and effect. Randomly assigning experimental units (for example, participants in a clinical trial) to treatment and control groups balances the two groups so as to minimize the chance of substantive differences between them other than those caused by any...
Data access is fundamental to JMP. For the last several releases, we've been building infrastructure so that you can access data efficiently, regardless of where it lives. Once you to get the data you need into JMP, you can begin answering the questions you have. Every version of JMP adds new efficiency gains, performance improvements, and workflow additions. JMP 19 continues that trend.
Prefer vi...
JMP 19 brings many improvements for Graph Builder. Here are a few of the most significant additions. Constrained smoothers The smoother element has a new method called P-Spline. It’s a cubic spline, just like the existing Spline method, but it’s parameterized in a way that better supports constraints. Monotonic trend curves are the most requested smoother feature, and now it’s possible – and then ...
JMP’s latest release brings a fresh wave of updates to the Design of Experiments (DOE) platform, with new tools and smarter workflows that make it easier to design, simulate, and explore experiments. Whether you're screening factors, simulating responses, planning sample sizes, or trying to pinpoint the root cause of a failure, there’s something new to try out. Smarter fault localization with Baye...
Data tables come in many sizes. Occasionally, I work with a table that is small enough to fit on screen: no scrolling necessary and everything I need, I can see. Most of the time, however, my data tables are tall, wide, complex, and multifaceted. For tables like these, the new data table organization and filtering tools in JMP shine. Let’s explore some real data to see why. I’ve been a longtime fa...
JMP’s latest release builds on the Python integration support that was introduced in JMP 18 by focusing on a fundamental part of the workflow: data access. By expanding data table operations and Python-JSL interoperability, accessing data becomes simple and convenient. Prefer video? Watch it here. Data Table operations The jmp.from_dataframe() function provides an efficient way to convert exte...
Overview If you have control chart warnings, you may want to: Get notifications about warnings that nobody has investigated yet.Assign warnings to another user, or to a user group, for investigation.Stay on top of the warnings that are assigned to you for investigation.Stay focused on the processes that still need attention.Know what happened, who dealt with it, and when by reviewing and downloadi...
Every pharmaceutical manufacturer needs to monitor its manufacturing facilities for possible contaminants from the environment. Mold from airborne spores and bacteria on surfaces are two of the threats that can ruin a batch. Other kinds of factories, like in the semiconductor industry, are threatened by airborne particulates. These facilities have specialized collection devices for environmental m...