The study aims to analyze the most productive Pakistani authors by using scientometric approach based on the Web of Science (WoS) data to perform group level comparative analysis. One hundred most productive authors have been recognized from ten years data of top ten universities ranked in WoS. Their publication data has been extracted for further analysis. We applied traditional metrics, h-index, h-type and composite indices. The authors have been divided into four groups, named Top Authors (N=31), Big Producers (N=18), Selective Authors (N=19) and Low Productive Authors (N=32). Descriptive and inferential statistics were performed.

Findings revealed that h-index, h-type and composite indices clearly differentiate upper and lower groups. However, the discrimination between middle groups is indistinct. The functional relationship of total citations of all groups with the h-type and composite indices is found better as compared to the other traditional metrics. Total citations of top authors, selective authors and low productive authors has strong relationship with g-index and p-index except big producers. Moreover, total citations has strong relationship with h-index at top author level, moderate relation with big producers and low productive authors and poor at selective author level. The relationship of citations per publications of all groups with the h-type and composite indices was found moderate or poor except p-index. It was observed that publications counts of all groups has weak relationship with all indices.

The study adds insight into the discrimination of groups of Pakistani authors using different scientometric indices. It may be of interest to those concerned in research performance evaluation metrics.

该研究旨在通过使用基于科学网络 (WoS) 数据的科学计量方法进行群体级别的比较分析，从而分析最具生产力的巴基斯坦作者。从 WoS 排名前十的大学的十年数据中，已经认可了 100 位最有生产力的作者。他们的发表数据已被提取以供进一步分析。我们应用了传统指标、h-index、h-type 和复合指数。作者被分为四组，分别是顶级作者 (N=31)、大制作者 (N=18)、选择性作者 (N=19) 和低生产力作者 (N=32)。进行了描述性和推理性统计。

调查结果显示，h 指数、h 型指数和综合指数清楚地区分高低组。然而，中间群体之间的歧视是模糊的。与其他传统指标相比，发现所有组的总引用次数与 h 型和复合指数的函数关系更好。除了大作者之外，顶级作者、选择性作者和低生产力作者的总引用与 g-index 和 p-index 有很强的相关性。此外，总被引次数与顶级作者水平的 h-index 相关性强，与大生产者和低产作者的关系中等，而在选择性作者水平上则较差。除 p 指数外，所有组的每篇出版物的引用与 h 型指数和复合指数的关系中等或较差。

该研究增加了对使用不同科学计量指标的巴基斯坦作者群体的歧视的洞察力。那些关注研究绩效评估指标的人可能会感兴趣。